National Park Service 

U.S. Department of the Interior 

Natural Resource Program Center 

Inventory and Monitoring Program

Data Management Guidelines for Inventory and 

Monitoring Networks 

Natural Resource Report NPS/NRPC/NRR—2008/035 
ON THE COVER 

Mesa Arch, Canyonlands National Park. NPS Photo 
Inventory and Monitoring Program

Data Management Guidelines for Inventory and 

Monitoring Networks 

Natural Resource Report NPS/NRPC/NRR—2008/035 

National Park Service 

Natural Resource Program Center 

Office of Inventory, Monitoring, and Evaluation 

1201 Oakridge Drive, Suite 150 

Fort Collins, Colorado 80525 

 

May 2008 

U.S. Department of the Interior 

National Park Service 

Natural Resource Program Center 

Fort Collins, Colorado 
__________________________________________________________________________ 

ii 

The Natural Resource Publication series addresses natural resource topics that are of interest 

and applicability to a broad readership in the National Park Service and to others in the 

management of natural resources, including the scientific community, the public and the NPS 

conservation and environmental constituencies. Manuscripts are peer-reviewed to ensure that 

the information is scientifically credible, technically accurate, appropriately written for the 

intended audience and is designed and published in a professional manner. 

Natural Resource Reports are the designated medium for disseminating high priority, current 

natural resource management information with managerial application. The series targets a 

general, diverse audience and may contain NPS policy considerations or address sensitive 

issues of management applicability. Examples of the diverse array of reports published in this 

series include vital signs monitoring plans; "how to" resource management papers; 

proceedings of resource management workshops or conferences; annual reports of resource 

programs or divisions of the Natural Resource Program Center; resource action plans; fact 

sheets; and regularly-published newsletters. 

Views, statements, findings, conclusions, recommendations, and data in this report are solely 

those of the author(s) and do not necessarily reflect views and policies of the U.S. 

Department of the Interior, National Park Service. Mention of trade names or commercial 

products does not constitute endorsement or recommendation for use by the National Park 

Service. 

Printed copies of reports in these series may be produced in a limited quantity and they are 

only available as long as the supply lasts. This report is also available from the Natural 

Resource Publications Management website (www.nature.nps.gov/publications/NRPM) on 

the Internet, or by sending a request to the address on the back cover. 

Please cite this publication as: 

National Park Service. 2008. Data management guidelines for inventory and monitoring 

networks. Natural Resource Report NPS/NRPC/NRR—2008/035. National Park Service, 

Fort Collins, Colorado. 

NPS D-1968, May 2008 
___________________________________________________________________________ 

iii 

Contents 

Page 

List of Tables ......................................................................................................................... vii

List of Figures ........................................................................................................................ vii

List of Appendices .................................................................................................................. vii

Change History ........................................................................................................................ ix

Acknowledgements ................................................................................................................... x

CHAPTER 1. Introduction ....................................................................................................... 1

1.1 Background ............................................................................................................... 1

1.2 Objectives of this Document ..................................................................................... 2

1.3 Organization .............................................................................................................. 3

1.4 Key Terms and Definitions ....................................................................................... 4

1.5 Types of data covered by this document................................................................... 5

1.6 Data Sources and Priorities ....................................................................................... 6

1.7 Maintenance of this Document ................................................................................. 7

1.8 References and Resources ......................................................................................... 7

1.9 Related Network-level SOPs .................................................................................... 7

CHAPTER 2. Infrastructure and Systems Architecture ........................................................... 9

2.1 Objectives ................................................................................................................. 9

2.2 Laws and Policies ..................................................................................................... 9

2.3 General Standards and Guidelines .......................................................................... 10

2.4 Infrastructure ........................................................................................................... 10

2.5 Systems Architecture .............................................................................................. 13

2.6 National Applications ............................................................................................. 17

2.7 Service-oriented Architecture and the Next Generation of National Applications 20

2.8 References and Resources ....................................................................................... 21

2.9 Related Network-level SOPs .................................................................................. 24

CHAPTER 3. Project Management and the Data Life Cycle ................................................ 25

3.1 Objectives ............................................................................................................... 25

3.2 Laws and Policies ................................................................................................... 25

3.3 General Standards and Guidelines .......................................................................... 25

3.4 Stages of Project Development ............................................................................... 26

3.5 The Data Life Cycle ................................................................................................ 29

3.6 References and Resources ....................................................................................... 31

3.7 Related Network-level SOPs .................................................................................. 31

CHAPTER 4. Data Management Roles and Responsibilities ................................................ 33

4.1 Objectives ............................................................................................................... 33

4.2 Laws and Policies ................................................................................................... 33

4.3 General Standards and Guidelines .......................................................................... 33

4.4 Specific Data Management Roles and Responsibilities .......................................... 34

4.5 References and Resources ....................................................................................... 38

4.6 Related Network-level SOPs .................................................................................. 38
__________________________________________________________________________ 

iv 

CHAPTER 5. Databases ........................................................................................................ 39

5.1 Objectives ............................................................................................................... 39

5.2 Laws and Policies ................................................................................................... 39

5.3 General Standards and Guidelines .......................................................................... 39

5.4 Database Planning and Workflow .......................................................................... 41

5.5 Data Modeling ........................................................................................................ 43

5.6 Other Database Considerations ............................................................................... 46

5.7 References and Resources ....................................................................................... 47

5.8 Related Network-specific SOPs .............................................................................. 47

CHAPTER 6. Data Acquisition, Processing, and Reporting ................................................. 49

6.1 Objectives ............................................................................................................... 49

6.2 Laws and Policies ................................................................................................... 49

6.3 General Standards and Guidelines .......................................................................... 49

6.4 Programmatic Data ................................................................................................. 49

6.5 Non-programmatic Data ......................................................................................... 53

6.6 Data Analysis and Reporting .................................................................................. 56

6.7 Changes to Procedures ............................................................................................ 57

6.8 References and Resources ....................................................................................... 57

6.9 Related Network-level SOPs .................................................................................. 57

CHAPTER 7. Quality Assurance and Quality Control .......................................................... 59

7.1 Objectives ............................................................................................................... 59

7.2 Laws and Policies ................................................................................................... 59

7.3 General Standards and Guidelines .......................................................................... 60

7.4 Project Planning and Data Design .......................................................................... 62

7.5 Data Collection ....................................................................................................... 62

7.6 Data Entry ............................................................................................................... 63

7.7 Data Verification and Validation ............................................................................ 64

7.8 Review, Conformance, and Communication .......................................................... 66

7.9 Roles and Responsibilities ...................................................................................... 67

7.10 References and Resources ....................................................................................... 68

7.11 Related Network-level SOPs .................................................................................. 68

CHAPTER 8. Data Documentation ....................................................................................... 69

8.1 Objectives ............................................................................................................... 69

8.2 Laws and Policies ................................................................................................... 69

8.3 General Standards and Guidelines .......................................................................... 70

8.4 Metadata Tools ........................................................................................................ 73

8.5 Work Flow Process ................................................................................................. 74

8.6 References and Resources ....................................................................................... 74

8.7 Related Network-level SOPs .................................................................................. 75

CHAPTER 9. Data Ownership and Sharing .......................................................................... 77

9.1 Objectives ............................................................................................................... 77

9.2 Laws and Policies ................................................................................................... 77

9.3 General Standards and Guidelines .......................................................................... 78

9.4 References and Resources ....................................................................................... 80
___________________________________________________________________________ 

v 

9.5 Related Network-level SOPs .................................................................................. 81

CHAPTER 10. Data Dissemination ..................................................................................... 83

10.1 Objectives ............................................................................................................... 83

10.2 Laws and Policies ................................................................................................... 83

10.3 General Standards and Guidelines .......................................................................... 84

10.4 Data Distribution Mechanisms ............................................................................... 84

10.5 References and Resources ....................................................................................... 87

10.6 Related Network-level SOPs .................................................................................. 88

CHAPTER 11. Records Management, Data Maintenance, and Archiving ......................... 89

11.1 Objective ................................................................................................................. 89

11.2 Laws and Policies ................................................................................................... 89

11.3 General Standards and Guidelines .......................................................................... 90

11.4 References and Resources ....................................................................................... 97

11.5 Related Network-level SOPs .................................................................................. 98

CHAPTER 12. Project Tracking and Documentation ......................................................... 99

12.1 Objectives ............................................................................................................... 99

12.2 Laws and Policies ................................................................................................... 99

12.3 General Standards and Guidelines .......................................................................... 99

12.4 References and Resources ..................................................................................... 100

12.5 Related Network-level SOPs ................................................................................ 100

CHAPTER 13. Implementation ......................................................................................... 101

13.1 Objectives ............................................................................................................. 101

13.2 Laws and Policies ................................................................................................. 101

13.3 General Standards and Guidelines ........................................................................ 101

13.4 Education and Training ......................................................................................... 102

13.5 Milestones ............................................................................................................. 102

13.6 References and Resources ..................................................................................... 102

13.7 Related Network-level SOPs ................................................................................ 102
__________________________________________________________________________ 

vi 
___________________________________________________________________________ 

vii 

Tables 

Table 1-1. Categories of data products and project deliverables ...............................................6

Table 4-1. Categories of data stewardship. ..............................................................................34

Table 6-1. Summary of possible data sources for different types of information and 

repositories where they are maintained .................................................................55

Table 10-1. Distribution mechanisms for I&M network-related data .....................................85

Figures 

Figure 1-1. Map showing the names and boundaries of the 32 I & M Program networks. .......1

Figure 1-2. Relationship of the national-level data management guidelines to network-level 

data management documents ..................................................................................3

Figure 2-1. Generalized infrastructure components. Dotted arrow depicts ability to log in 

remotely. ...............................................................................................................11

Figure 3-1. Data management steps during the five stages of project development. Key data 

management activities are in bold type. ................................................................27

Figure 3-2. The data life cycle. ................................................................................................29

Figure 4-1. The overlap between data management responsibilities of the project leader and 

data manager. ........................................................................................................37

Figure 5-1. Different levels of data standards and their corresponding degree of 

variability. .............................................................................................................41

Figure 5-2. Monitoring database application development process. Stages shown in blue 

represent tasks that require specific input from scientists to guide the database 

development process. ............................................................................................42

Figure 5-3. The triple constraint triangles ................................................................................46

Figure 7-1. General course of data and associated quality assurance/quality control 

procedures. ............................................................................................................61

Figure 7-2. Some common information management elements influencing the amount of 

QA/QC needed. .....................................................................................................62

Figure 8-1. Local and national applications and tools for metadata ........................................74

Figure 10-1. Flow diagram for water quality data from I&M networks to the STORET 

 National Data Warehouse. ..................................................................................86

Figure 11-1. General workflow for storage and archiving of electronic (blue) and hard copy 

 (green) scientific research products. ....................................................................93

Appendices 

Appendix A. Glossary of Terms 

Appendix B. List of Acronyms 

Appendix C. Checklist for completing or updating network-level data management plans 
__________________________________________________________________________ 

viii 
___________________________________________________________________________ 

ix 

Change History

Version numbers will be incremented by a whole number (e.g., Version 1.3 to Version 2.0) 

when a change is made that significantly affects requirements or procedures. Version 

numbers will be incremented by decimals (e.g., Version 1.6 to Version 1.7) when there are 

minor modifications that do not affect requirements or procedures included in the plan. 

The following revisions have occurred to this plan since May 30, 2008 

Version # Date Revised by Changes Justification 

1.1 8 July 08 J. Bennett Formatting To Follow NRR 

formatting guidelines 

more closely 

1.2 11 May 08 J. Bennett minor formatting 

updates 

 
__________________________________________________________________________ 

x 

Acknowledgements 

This document is truly a product of many efforts. The community of Inventory and 

Monitoring Program data managers is an unprecedented assemblage of talent that is 

contributing much to the advancement of data and information management within the 

National Park Service. This group has fostered a collaborative environment with the free 

sharing of information and ideas for the benefit of all. 

Persons who have developed and contributed material presented in this plan and who deserve 

specific credit include: Debbie Angell, Margaret Beer, John Boetsch, Kristina Callahan, Rose 

Cook, Vel Decker, Gordon Dicus, Fred Dieffenbach, Patrick Flaherty, Brent Frakes, Ulf 

Gafvert, Whitney Granger, Mark Hart, Pat Lineback, Scott Miller, Sean Mohren, Dorothy 

Mortenson, Nathan Piekielek, Dave Press, Tom Richie, Gareth Rowell, Geoff Sanders, 

Dennis Skidds, Heidi Sosinski, Sara Stevens, Leona Svancara, Nicole Tancreto, Helen 

Thomas, Bob Truitt, Doug Wilder, Mike Williams, Brian Witcher, and Christina Wright. 

In addition, national-level data management staff have provided the vision and created the 

tools that have been essential to our work. In particular, our thanks go to Peter Budde, Chris 

Dietrich, Kathy Dratch, Joe Gregson, Willene Hendon, Simon Kingston, Alison Loar, 

Danelle Malget, Lisa Nelson, Wendy Schumacher, and Mark Wotawa for their support, hard 

work, and dedication. 

We thank Gary Williams, who has administered the I&M Program with a careful and steady 

hand over the years. 

Finally, we thank Steve Fancy for his ongoing commitment to data management in the 

National Park Service, and for the insight and guidance he has provided to all of us. 
_____________________________________________________________________________ Chapter 1 – Introduction 1

CHAPTER 1. Introduction 

1.1 Background 

Information is the common currency among the activities and staff involved in natural resource 

management in the National Park Service (NPS). The central mission of the National Park 

Service’s Inventory and Monitoring (I&M) Program is to acquire, manage, analyze, and 

distribute scientific information on the status and trends of specific park natural resources 

(National Park Service 1998). Intended users of this information include park managers, 

planners, cooperators, researchers, and the general public. 

Under the program, more than 270 park units with significant natural resources have been organized into 32 I&M networks to facilitate baseline inventories and to conduct long-term resource 

monitoring (Figure 1-1). Each network links parks that share similar geographic and natural 

resource characteristics to improve efficiency and reduce costs. Parks within a network share 

funding and professional staff to avoid duplication of efforts. 

Figure 1-1. Map showing the names and boundaries of the 32 I & M Program networks. 

A cornerstone of the I&M Program is the strong emphasis placed on data management. Data 

management refers to the framework by which data are acquired, maintained, and made 

available. A robust data management system is particularly important for the success of longterm programs where the lifespan of a data set will extend across the careers of many scientists. 

All I&M networks are expected to invest at least one-third of their available resources in data 

management, analysis, and reporting activities. 
_________________________________________________________________________ 

2 

The goal of each network’s data management program is to maintain, in perpetuity, the 

ecological data and related analyses that result from the network’s resource inventory and 

monitoring work. The purpose of this document is to describe the overarching policies relevant 

to network data management, to establish objectives common to all networks, and to provide 

national guidance that will ensure the highest standards for data acquired and managed by all 

networks. These standards include: 

Accuracy: The quality of the data collected and managed by the I&M Program is paramount. 

Analyses performed to detect ecological trends or patterns require data with minimal error and 

bias. Inconsistent or poor-quality data can limit the detectability of subtle changes in ecosystem 

patterns and processes, lead to incorrect interpretations and conclusions, and could greatly 

compromise the credibility and success of the I&M Program. To ensure that networks produce 

and maintain data of the highest possible quality, procedures are established to identify and 

minimize errors at each stage of the data life cycle. 

Security: Digital and hard-copy data must be maintained in environments that protect against 

loss, either due to electronic failure or to poor storage conditions. Networks must have in place 

proper storage and backup procedures and disaster recovery plans, as well as established records 

management process. In addition, collaboration with the NPS Museum Management Program 

enlists the expertise of museum curators and archivists to ensure that related project materials 

such as field notes, data forms, specimens, photographs, and reports are properly cataloged, 

stored, and managed in archival conditions. 

Longevity: Countless data sets have become unusable over time either because the format is 

outdated, or because metadata is insufficient to determine the data’s collection methods, scope 

and intent, quality assurance procedures, or format. While proper storage conditions, backups, 

and migration of data sets to current platforms and software standards are basic components of 

data longevity, comprehensive data documentation is equally important. Networks must ensure 

that data sets are consistently documented, and in formats that conform to current federal 

standards. 

Usability: One of the most important responsibilities of the Inventory and Monitoring Program 

is to ensure that data collected, developed, or assembled by staff and cooperators are made 

available for decision-making, research, and education. Providing well-documented data in 

appropriate formats and in a timely manner to park managers is especially important to the 

success of the program. Networks must ensure that: 

 data can be easily found and obtained 

 data are subjected to full quality control before release 

 data are accompanied by complete metadata 

 data are provided in formats that are most useful to end users 

 sensitive data are identified and protected from unauthorized access and distribution. 

1.2 Objectives of this Document 

This concept of a national-level data management plan was developed as the result of over 25 

individual network plans being written between 2003 and 2006. Network data managers realized 

that significant portions of their plans were common to all networks; in particular, sections 
_____________________________________________________________________________ Chapter 1 – Introduction 3

describing the overarching objectives and policies. By establishing a national-level plan 

containing these common elements, network data managers could concentrate instead on 

establishing, documenting, and updating their specific network-level guidelines and standard 

operating procedures (SOPs). 

This document, which establishes national-level data management guidance, is intended as a 

reference that guides and complements the specific procedures that are developed by each 

network. This plan outlines the I&M Program’s approach to establishing and maintaining 

systems that serve the data management needs of the networks, their member parks, and the 

national I&M Program. It is intended to be a guide for current and future network staff, to ensure 

the continuity and documentation of data management methods and procedures, to establish best 

practices, and to provide a baseline of standards common to all networks. 

Network data management plans are intended to broadly describe how the national plan will be 

implemented at the network level, provide general orientation on a network’s data management 

program (e.g., infrastructure, staffing), and direct the reader to more detailed guidance 

documents and SOPs (Figure 1-2). 

Figure 1-2. Relationship of the national-level data management guidelines to network-level data 

management documents 

Network data management guidelines typically contain explanations of procedures that apply to 

multiple situations; for example, file or field naming, backup and restore procedures, or website 

management. Protocols and SOPs provide an additional level of detail, with step-by-step 

procedures for situations where there is little or no tolerance for variation. Together these 

documents and procedures ensure that processes that are critical for I&M network continuity and 

data integrity are maintained, even in the event of staff or program changes. 

1.3 Organization 

This document offers a guide for I&M network programs and provides the foundation for 

implementing and maintaining data management systems and best practices. Each of the chapters 

contains the following sections: 

National Data 

Management Guidance 

Network Data 

Management Plan 

Network Guidelines, 

Protocols, and SOPs 

General 

Specific 
_________________________________________________________________________ 

4 

 Objectives: Specific statements describing the results to be achieved by the procedures 

contained within the chapter 

 Laws and Policies: Requirements and sideboards established through laws, policies, and 

mandates at different levels of governance, ranging from broad federal law, to 

Department of Interior (DOI) and NPS policies, to policies developed specifically for the 

Inventory and Monitoring Program. 

 General Standards and Guidelines: Generally-accepted I&M network standards and 

guidelines applicable to specific chapters. 

 References and Resources: Citations of or links to specific laws, policies, or documents 

pertinent to chapter content. 

 Related Guidance Documents and/or SOPs: A listing of network-level guidance or 

procedural documents that may be needed to accomplish the stated chapter objectives. 

1.4 Key Terms and Definitions 

Since the principal purpose of this document is to provide standards and guidelines for the 

development, management, and dissemination of data, it is important to apply consistent 

terminology. A glossary of terms and acronyms used both within this report and by I&M 

networks can be found in Appendix A; however, the following definitions of general terms 

provide the basis for key concepts in this and following chapters: 

Data are distinct measurements or observations of a variable, usually formatted in a special way: 

they include symbols or representations of facts or ideas that can be communicated, interpreted, 

or processed by manual or automated means. 

Raw data are data in their original form, i.e., data that have not been altered, summarized, or 

grouped into broader categories. Raw data can exist in many forms: as hand-written information 

on field data forms and in notebooks, as unaltered photographs, sound and video recordings, data 

logger files, remote sensing imagery, and Global Positioning System (GPS) files. They may be 

typed or uploaded directly into a computer upon acquisition, or transcribed later from data 

sheets. 

Derived data are raw data that have been processed, or converted to another form using some 

automated or manual process. Raw natural resources data are often processed and packaged for 

summation, statistical analysis, and graphical display, or the production of maps and other 

information products. 

Information is created from data as a result of processing, manipulating, synthesizing, or 

organizing data in a way that provides interpretation or meaning. 

Tabular data are usually organized into logical tables of records and attributes, arranged in a 

matrix of rows and columns. Tabular data can be displayed, manipulated, and stored as simple 

text files or in applications software (e.g., spreadsheets, relational databases). 

Spatial data are any data that reference geographic coordinates. Tabular data that contain spatial 

references are also considered spatial. For example, a table of wildlife observations might 

include the x and y coordinates of the location of observation, along with other information, such 

as species identifier, observer name, and date of observation. 
_____________________________________________________________________________ Chapter 1 – Introduction 5

GIS (geographic information systems) data contain information about the location and shape of, 

and relationships among, features on the surface of the earth and are usually stored as geographic 

coordinates and topology. Topology is used to compare the geographic locations of features 

relative to one another (e.g., roads connected to a highway, two vegetation polygons adjacent to 

one another). GIS data can be categorized as either vector or raster and require specific software 

applications for processing and manipulation. 

Legacy data are existing data that may be at risk of becoming obsolete due to software or 

metadata limitations, technological changes, or the loss of institutional knowledge. 

Programmatic data are data developed specifically for a project with well-defined objectives and 

specific requirements describing data use and application. As an example, satellite imagery may 

be acquired for a geographic area to provide an analytical data framework for monitoring 

landscape change over a period of time. 

Non-programmatic data are data developed by other programs or organizations, but that are of 

value in meeting network objectives. For example, weather data acquired by the National 

Weather Service, or taxonomic information managed by the US Department of Agriculture. 

Sensitive data are data that through loss, unauthorized access, or modification, could be used in 

such as way as to adversely affect valuable resources, the national interest, the conduct of federal 

programs, or individual privacy. Examples of sensitive natural resources data might include the 

locations of rare flora or fauna species, caves, or cultural sites. 

Metadata are information about data. A complete set of metadata describes all aspects of the 

subject data, including the who, what, where, when, how, and why of a data set, along with any 

processing that has occurred. Metadata are considered an essential component of any good data 

set. The term also applies to the synoptic information for a document, publication, sample, or 

other physical material.

1.5 Types of data covered by this document 

Data must be accompanied by sufficient context about how and why they were collected if they 

are to maintain their long-term value. A data management program cannot simply attend to the 

resulting tables, fields, and values that make up a data set; there must also be a process for 

developing, preserving, and integrating the context that makes the data usable. To maintain this 

context, this document encompasses a range of products that are coordinated or managed by 

networks or under their auspices. These products fall into six general categories: raw data, 

derived data, information, documentation, reports, and administrative records (Table 1-1). 
_________________________________________________________________________ 

6 

Table 1-1. Categories of data products and project deliverables 

Category Examples 

Raw data GPS files, raw field forms and notebooks, photographs and 

sound/video recordings, telemetry or remote-sensed data files, 

biological voucher specimens 

Compiled/derived 

data 

Relational databases, tabular data files, GIS layers, maps, species 

checklists, output files 

Information Products derived from the processing, manipulation, synthesis, or 

organization of data that provides interpretation and meaning 

Documentation Data collection protocols, data processing/analysis protocols, record 

of protocol changes, data dictionary, metadata, data design 

documentation, quality assurance report, catalog of 

specimens/photographs 

Reports Annual progress report, final report (technical or general audience), 

periodic trend analysis report, publication 

Administrative 

records 

Contracts and agreements, study plan, research permit/application, 

other critical administrative correspondence 

1.6 Data Sources and Priorities 

There are multiple sources of data related to natural resources in network parks. The types of 

work that may generate these data include: 

 natural resource inventories 

 vital signs monitoring 

 protocol development pilot studies 

 special-focus studies performed by internal staff, contractors’ or cooperators’ external 

research projects, or studies performed by other agencies on park or adjacent lands 

 resource impact evaluations related to park planning and compliance 

 resource management and restoration work. 

Because the I&M Program focuses on natural resource inventories and long-term monitoring, a 

network’s first data management priority is the data and information that result from these 

efforts. However, the standards, procedures, and approaches to data management developed by 

networks can also applied to other natural resource data sources. 

Considering the volume of data that has been produced in park units, priorities must be set for 

network data management efforts. As a general rule these are: 

1. Produce and curate high-quality, well-documented data originating with the Inventory and 

Monitoring Program 

2. Assist with data management for current projects, legacy data, and data originating outside 

the Inventory and Monitoring Program that complement program objectives 
_____________________________________________________________________________ Chapter 1 – Introduction 7

3. Help ensure good data management practices for park-based natural resource-related projects. 

1.7 Maintenance of this Document 

This document will be updated as needed to accommodate the inevitable changes that will occur 

in laws, policies, technology, or general data management practices. Recommendations for 

changes can be forwarded to the national Inventory and Monitoring Program data manager by 

any interested party or user of this document (e.g., park resource managers, project leaders, 

technicians, superintendents, external users). Simple changes can be made immediately in the 

document, while substantive changes will be made during version updates and in consultation 

with network data managers. 

Document versions will be designated by using version numbers in parentheses that are 

appended to the heading of the modified section. For example, the first version of a section in 

Chapter 4 would have the heading “4.1.” A revision to this section would have the heading 

“Chapter 4. (v2).” The Change History log at the front of this document contains an update 

schedule and key that identifies and summarizes changes. Previous versions will be archived in 

their entirety for reference. 

A working version of this document will be available on the Natural Resource Program Center 

SharePoint site: (http://nrpcsharepoint). Finalized versions will be available on the Inventory and 

Monitoring Program Internet site (http://science.nature.nps.gov/im/datamgmt). 

1.8 References and Resources 

National Park Service. 1998. National Parks Omnibus Management Act of 1998. Public Law 

105-391. (http://www.nps.gov/legal/laws/105laws.htm) 

National Park Service. 1999. Natural Resource Challenge: the National Park Service’s action 

plan for preserving natural resources. (http://www.nature.nps.gov/challenge/) 

National Park Service. Natural Resource Program Center SharePoint. (http://nrpcsharepoint). 

Accessed 16 January 2008. 

National Park Service. 1999. Natural Resources Inventory & Monitoring. Director’s Order #70, 

NPS-75. (http://www.nature.nps.gov/nps75/nps75.pdf) 

National Park Service. Natural Resources Inventory & Monitoring Program, data management. 

(http://science.nature.nps.gov/im/datamgmt). Accessed 16 January 2008. 

1.9 Related Network-level SOPs 

 Development and review process for network guidance documents 

 Template for network SOPs 
_________________________________________________________________________ 

8 
______________________________________________________________________ 

Chapter 2 – Infrastructure and Systems Architecture 9 

CHAPTER 2. Infrastructure and Systems Architecture 

Modern information management infrastructure and systems architecture represent the 

foundation of network information management systems. Infrastructure refers to the system 

of computers, servers, and related hardware that is functionally or directly linked through 

computer networking services. Systems architecture refers to the applications, database 

systems, repositories, and software tools that make up the framework of a network’s 

information management enterprise. 

2.1 Objectives 

The objectives of proper management, configuration, and maintenance of I&M network 

infrastructure and systems architecture are: 

 Ensure staff has appropriate access to electronic files that are secure and protected from 

accidental or malicious loss 

 Simplify software installation and management, and expedite access and retrieval of data 

using automation tools 

 Make available collaborative technologies and tools that enhance networking and 

communications at both an intra- and interagency level 

 Develop and implement efficient means for storing, managing, searching, and 

disseminating electronic files. 

2.2 Laws and Policies 

The Department of Interior (DOI) and National Park Service (NPS) have established 

guidelines and standards for the acquisition, configuration, and deployment of hardware and 

software in I&M network offices. Specifically: 

 All DOI agencies are required to standardize on Microsoft Office products for 

desktop application and use of spreadsheets, documents, databases, and presentation 

software (DOI, Chief Information Officer, November 30, 2005). 

(http://www.doi.gov/ocio/erm/software.html)

 All DOI agencies are required to standardize on ESRI products when using GIS 

software (DOI, Chief Information Officer, November 30, 2005). 

(http://www.myinterior.doi.net/ocio/cto/ctoc/Version3.1/ProductsByStandard.pdf)

 All DOI agencies, including the NPS, are required to limit administrative rights to 

servers and computers to those staff that are required for operational use. All users 

with administrative rights must have an approved request, with justification, on file 

with the agency’s Office of Chief Information Office (OCIO) 

(http://classicinside.nps.gov/documents/OCIO%202005-0004.doc). 

 Local and wide area networks (LAN/WAN) should conform to Department of 

Interior and National Institute of Standards and Technology (NIST, SP800-53) 

security guidelines (http://csrc.nist.gov/publications/drafts/800-53A/draft-SP800-

53A-fpd-sz.pdf). 
_________________________________________________________________________ 

10 

In general, I&M networks will conform to any federal, department, agency or bureau data 

infrastructure and systems architecture policies and standards. Further, I&M staff will 

conform to national I&M Program standards and mandates to ensure long-term program 

integration and information sharing. 

2.3 General Standards and Guidelines 

I&M networks situated within an NPS office typically rely on park, regional, and national 

information technology (IT) personnel and resources to maintain their computer 

infrastructure and systems architecture. Local park IT specialists are primarily responsible for 

development and management of local infrastructure with oversight and support from 

regional and national IT programs. Development and management of network architecture is 

broadly distributed among local, regional and national IT staffs and direct participation by 

other local and national programs including GIS and I&M staffs. 

I&M networks that are hosted by a university or other government agency or organization 

must collaborate closely with the host in addressing the network’s infrastructure needs. 

Typically this means that an I&M network’s local area network (LAN) or each individual 

computer is connected to a larger LAN or wide area network (WAN) that is maintained by 

the university or other agency/organization. An agreement is recommended that designates 

network staff as a point of contact and that staff computers are to be maintained as part of the 

larger network. The larger host network infrastructure or IT Plan should be referenced in 

network SOPs so that responsibilities for servers, backup and archiving, Internet connections, 

and other fundamental services are clearly articulated and understood. 

Core infrastructure and systems architecture capabilities for I&M networks should include: 

 A network directory structure with a decentralized security system allowing 

appropriate individuals the ability to manage and maintain file security permissions 

 Data structures and data models that optimize flexibility and scalability and integrate 

with other national applications. 

 Software tool(s) that simplify and streamline staff access to spatial data and metadata. 

 Installation of software, patches, updates, and tool extensions that is automated and 

delivered through software installation and management portals 

 Reliable high-speed connectivity to the Internet 

 Active Directory accounts for all NPS staff and key cooperators to enable access to 

internal NPS data resources. 

2.4 Infrastructure 

The foundation of an information management program is a reliable and secure network of 

computers, servers and an associated backup schema. Other than personal computers, I&M 

networks may or may not have separate computer infrastructure including file or application 

servers. 

There are multiple components associated with the NPS infrastructure including park, 

network, regional, and national level systems (Figure 2-2). Each level can be the repository 

of different components of the information system that are maintained and secured by the 
______________________________________________________________________ 

Chapter 2 – Infrastructure and Systems Architecture 11 

respective IT, resource specialists and/or other responsible staff. This includes hosting and 

managing electronic files being created, managed, and disseminated by staff and cooperators. 

Figure 2-1. Generalized infrastructure components. Dotted arrow depicts ability to log in 

remotely. 

2.4.1 Servers 

Computer servers may be broken into five primary functional types (one physical server may 

perform more than one of the functions listed below): 

 Work File Servers – Typically team servers or user servers, where anyone can store 

working files. These servers work similarly to a PC’s C: drive, but are located on a 

server for ease of backups and file sharing. 

 Data File Servers - Read-only repository of data files. Files stored here do not 

typically change often and need a consistent location, such as in the case of GIS data, 

imagery, or final reports. Write access is under strict control, whereas all NPS 

employees have read access. A contact person monitors what is stored in this location 

to ensure proper archiving and documentation. These servers are designed for large 

storage capacity. 

 Database Servers – Uses special database software, such as SQL Server, Oracle, or 

ArcSDE. Write access is under strict control. Databases on these servers are for longterm data storage, and require quality database design, documentation, and 

administration. 

 Application Servers –Provide the applications, or “front end,” to accessing the data. 

These are closely tied to the data file and database servers, but should be located on a 

different physical server. Files on these servers change frequently and backups need 
_________________________________________________________________________ 

12 

to support these changes. Application servers are often Internet servers as well. These 

servers are designed for speed. 

 Internet Servers – Provide access to applications and files via the Internet and subject 

to security restrictions. Special software may be used on Internet servers, such as 

ColdFusion for web site pages and database applications, and ArcIMS for Internet 

interactive mapping. 

It is not recommended that I&M networks establish public-facing application or Internet 

servers, which may require an extensive documentation and approval process through the 

NPS Chief Information Officer. Instead, these functions should be provided by the nationallevel I&M servers and infrastructure based in Fort Collins, Colorado. 

I&M networks will generally use or access one or more of the following servers: 

National-level Servers

National servers provide both secure (NPS only) and public workspaces that are accessible 

via the Internet. They are available to I&M networks for: 

 Master applications, e.g., integrated client-server versions of NatureBib, NPSpecies, 

Research Permit and Reporting System 

 Centralized repositories, e.g., NPS Data Store, Monitoring Protocol Database 

 Public access sites, e.g., web sites for monitoring networks 

 Enterprise-level tools such as SQL Server and SharePoint. 

Regional-level Servers (optional)

Depending upon the location of the network offices, regional servers may be used for 

specific functions. 

I&M network-level Servers

A network may have its own server(s) or be integrated into other units such as a park or 

cooperative institution. 

Local- or park-level Servers

In the majority of instances an I&M network is integrated into an existing park unit server(s). 

Local area networks provide shared workspace for staff, and also provide each staff member 

with dedicated workspace that is part of a regular backup routine. 

2.4.2 Workstations 

I&M network staff manage files on their personal computers, and, in most instances, place 

files that need to be shared on local server(s). Staff are responsible for regularly copying their 

workstation files to workspace to a network or external drive for backup. 

2.4.3 Local Administrative Rights 

The DOI and agency offices of the Chief Information Office are responsible for the guidance 

and oversight of administrative rights on computers and servers. Park, I&M network, and 

regional IT staff administer the guidance and issue rights as they apply on case-by-case 

bases; however, a principle of least privileges is to be applied as the best practice (OCIO 

2005-0004). (http://classicinside.nps.gov/documents/OCIO%202005-0004.doc) 
______________________________________________________________________ 

Chapter 2 – Infrastructure and Systems Architecture 13 

2.4.4 Network Security 

Local and wide area networks should conform to Department of Interior and National 

Institute of Standards and Technology (NIST, SP800-53) security guidelines. All sensitive 

electronic files should be placed in protected folders with limited read and write access. 

Electronic file and directory permissions administration should be partially decentralized 

with file and folder administrative rights controlled by limited I&M network. A method for 

tracking of file permissions is recommended. I&M network or park staff needing read or 

write access to the directory structure should be enabled through Microsoft Active Directory. 

There are rare circumstances where encryption of sensitive electronic files and/or folders 

may be necessary. As an example, files on removable media or portable devices may need 

additional protection from unauthorized access or use. NPS encryption policy and procedures 

are under development; data managers should work with a local IT specialist if this capability 

is required. 

2.5 Systems Architecture 

Integrated inventory and monitoring of natural resources is complex, multidisciplinary, and 

requires a broad suite of tools, cooperators, and standards for long-term success. 

2.5.1 Digital Data Formats 

Databases 

Well thought-out database design standards are necessary to promote compatibility among 

data sets, scalability, and long-term stability. As much as possible, I&M network standards 

for database design will mirror the NPS Natural Resource Database Template (NRDT). The 

NRDT is a flexible, relational database core designed for storing inventory, monitoring, and 

research data (including raw data collected during field studies). The template was designed 

to be used in the development of standalone databases; however, the basic structure can be 

implemented in enterprise-level systems (e.g., SQL Server) as well. NRDT also interacts 

with GIS software (e.g., ArcView or ArcGIS). See Chapter Five for additional information 

on NRDT. 

Tabular data 

Tabular data can exist in any number of applications (e.g., word processing, spreadsheets, 

databases) and formats (e.g., dat, txt, xml, dbf, xls, csv). Standardizing on the Microsoft 

Office Suite is required. When and where possible it is also strongly advised to document any 

attribute and table information. Additional guidance on this is provided in Chapter Eight. 

Spatial data 

I&M network and park unit staff use many different raster and vector data formats for storing 

and managing spatial data. Vector data formats commonly include Arc/Info coverages, 

shapefiles, and personal geodatabases. Raster data formats commonly include MRSID, TIFF, 

GEOTIFF, and Grid structures. ESRI (Environmental Systems Research Institute) software 

products have historically demonstrated excellent backward compatibility with older data 

structures; however it is recommended that data be migrated to current versions when 

possible. 
_________________________________________________________________________ 

14 

The coordinate system standard for the National Park Service is Universal Transverse 

Mercator with North American Datum 1983 (UTM NAD 83). Generally, existing spatial data 

should be migrated to this data projection and it should be used for any new spatial data 

development. 

With the release of ArcGIS 9.2, the file geodatabase is available. This data format has 

numerous advantages including: a) providing a relatively simple and scalable solution for 

GIS users; b) working across operating systems; c) scaling to handle very large data sets; d) 

an efficient data structure optimized for performance and storage; and e) increased flexibility 

for multi-user editing and use of the same spatial data layer. 

Image data 

Photographic information has become an important component of resource management, and 

can potentially consume considerable amounts of electronic storage resources. Photographic 

information in the forms of digital images, scanned photographs, and satellite imagery holds 

tremendous value and utility; however, the careful, long-term stewardship of these data along 

with appropriate documentation are both required to avert information loss. 

There are a number of photo or image management applications and software programs 

available both commercially off-the-shelf or easily designed and developed in a relational 

database. It is recommended I&M networks develop and adhere to a well-documented and 

disciplined image management schema in order to preserve these assets long-term. 

Audio and video media data 

Audio and video media can represent actual data values (e.g., hydrophone or Anabat 

recordings) and also have potential for various reporting and outreach purposes. The 

enabling technology for networked audio and video is easily available to those with a 

personal computer, and I&M networks will be increasingly taking advantage of this 

capability. SOPs that define the best formats and associated software, and address storage 

capacity issues, will be required as these media are more broadly used. 

2.5.2 Database Applications Development 

Rather than developing a single, integrated database system, most I&M network database 

design is based upon modular, standalone project databases that share design standards and 

links to centralized data tables. Individual project databases are developed, maintained, and 

archived separately. There are several advantages to this strategy: 

 Data sets are modular, allowing greater flexibility in accommodating the needs of 

each project area 

 Individual project databases and protocols can be developed at different rates without 

a significant cost to data integration 

 One project database can be modified without affecting the functionality of other 

project databases. 

Databases are recommended to be in Microsoft Access format, SQL Server, or other 

established industry-standard relational database management system (RDBMS). Databases 
______________________________________________________________________ 

Chapter 2 – Infrastructure and Systems Architecture 15 

produced under contract or cooperative agreement should also follow these 

recommendations. 

Also recommended is the development of an integrated data dictionary that will allow 

databases across projects and across disciplines to share common attributes whenever 

possible. Likely lists of standard attributes and values to be developed include: park unit 

codes, place names, watershed codes, species identifiers, and vegetation or land type 

classifications. To the extent possible, an I&M network can work with the Washington 

Support Office (WASO) and other networks to develop and use shared look-up tables for 

data consistency and inter-operability at a higher level across programs. 

2.5.3 Geographic Information Systems 

ESRI GIS applications and products are regularly used by NPS, and GIS is an essential 

component of an I&M network’s data management framework. 

For small park units where there are few, if any, resource staff, I&M network staff are 

encouraged to provide some level of spatial data management support. This may include 

assistance with documentation, archiving, data acquisition, and data dissemination as 

requested. In the case of network park units that are larger and have either dedicated GIS 

staff or collateral duty personnel, I&M networks should work in collaboration with these 

identified staff in support of spatial data relative to their park units. 

While most GIS programs at the park or I&M network level are run independently from one 

another, there are some common infrastructure solutions that are applicable across 

jurisdictional boundaries: 

 Automated GIS Software Installations and Updates: Because of the increasing 

numbers of GIS software users, it is most efficient to implement ESRI software 

installation protocols that streamline installation and updates, including silent updates 

for existing ArcGIS software users. Initial software installations should be completed 

through a flexible intranet portal, but future updates conducted through silent and 

bulk updates. 

 NPS Theme Manager: This ArcGIS extension, developed by the Alaska Regional 

Office, can be deployed and managed to deliver spatial data and metadata to staff. 

Theme Manager provides a front end for spatial data and makes it easier for staff to 

locate and access spatial data. The installation and management can be semiautomated, with updates rolled out to users each time they start a new ArcGIS project. 

2.5.4 Web Sites 

Web sites are a fundamental tool for providing information about the I&M Program and I&M 

networks. I&M web sites are hosted from a server at the NPS Natural Resource Program 

Center (NRPC) in Fort Collins. I&M networks are required to follow a common design 

standard for both their Internet and intranet sites that align with NPS web design guidelines. 

I&M network web sites are designed to provide information on inventories, vital signs 

monitoring, and data management. They also serve products such as the results of I&M vital 

signs monitoring (e.g., resource briefs, progress reports, trend reports), monitoring plans, data 
_________________________________________________________________________ 

16 

management plans, other documents and publications, and other items such as newsletters, 

calendars, and outreach materials. While standardized guidelines and formats provide a 

common look, feel, and navigation sequence for users, latitude is provided to accommodate 

individual network requirements or preferences. 

The structure and content of web sites must comply with National Park Service standards, 

FOIA requirements for accessibility of public information, and Section 508 of the 

Rehabilitation Act which ensures access to electronic information by persons with 

disabilities. Web development should adhere to the guidance posted on the national I&M 

intranet site, and to policies and guidance on natural resources web publishing provided in 

NPS Director’s Order #70 (National Park Service 2001). 

Sample Network page models for both Internet (publicly-facing) and intranet (NPS only) 

pages, and general web assistance are provided by WASO I&M support staff, along with 

security coding and support. The most current web guidance is posted on the I&M Data 

Management intranet (http://www1.nrintra.nps.gov/im/datamgmt/webdev/). 

Internet Sites 

The Internet web sites are designed to disseminate material that is relevant to the NPS 

mission of stewardship, preservation, education and protection of public resources. All 

network Internet sites and pages are hosted on servers located at WASO in Fort Collins. 

In order for I&M Internet sites to be relevant to the widest possible audience, high-level 

pages (i.e., home page and secondary pages) should provide general and summary content 

that provides background and context for the I&M Program and network. Links then provide 

paths to detailed information that may have a more limited or specialized readership. 

Network web designers should take into consideration the file size of images, maps, or 

documents that are posted, and adjust their content to avoid excessive download times. 

Intranet Sites 

The NPS intranet web (http://www1.nrintra.nps.gov/im/) sites are available only to those 

with access via either an NPS computer (authenticating by the user’s Active Directory login) 

or via a virtual private network (VPN) login. Intranet sites are intended to house information 

pertinent to NPS staff and cooperators, including data that may be preliminary, sensitive, or 

otherwise not appropriate for public distribution. All network intranet sites and pages are 

hosted on servers located at WASO in Fort Collins. 

Extranet Sites 

NPS security policies currently limit the availability of extranet capabilities (i.e., the ability 

for authenticated external cooperators to access internal NPS networks). NRPC continues to 

investigate possible solutions to these limitations and realizes the wide-reaching benefits of 

extranets. 

Personal Communications 

The use of email and telephones to conduct personal communication between individuals at 

separate locations is ubiquitous. Instant messaging is near real-time and offers additional 

flexibility for communicating with one or more employees. 
______________________________________________________________________ 

Chapter 2 – Infrastructure and Systems Architecture 17 

Collaboration Technologies 

The I&M Program is a widely-dispersed program requiring frequent and effective 

communication among staff and cooperators. Several NPS enterprise-wide tools are proving 

to be particularly useful: 

IBM Lotus Sametime Meeting 

Sametime allows presentations and content on a user’s computer to be shared with others 

within NPS. In combination with conference calling, Sametime can be an effective 

alternative to meetings requiring travel. Lotus Notes Sametime Meeting is currently available 

to all NPS employees with a NPS computer network login profile. 

http://np013denver.nps.gov 

Microsoft SharePoint

SharePoint is a web-based collaboration tool that allows multiple users to create, view or 

contribute to documents, surveys, wikis, discussion forums, and other types of projects that 

require the participation of many. Unlike web sites, all users with appropriate permissions, 

can easily post or contribute content. 

SharePoint requires setup and management by an IT network administrator, and instances are 

available through NRPC (http://nrpcsharepoint) and many regional NPS offices. In 2008, 

NRPC established a SharePoint site for I&M networks, which they may use as needed 

(http://imnetsharepoint). 

2.6 National Applications 

The basic tenet of I&M information management is to provide integrated natural resource 

databases and information systems that provide park staff with relevant, high-quality data for 

management decisions, resource protection, and interpretation. I&M information needs are 

broadly separated into two categories: 

 Detailed data and information needed for onsite resource management and 

protection. The information used to guide natural resource management decisions 

must be specific to inform and be useful to management staff at parks and central 

offices. 

 Summary information needed to describe the resources and their condition. This kind 

of information usually needs to be aggregated across the National Park Service for 

use by NPS and DOI managers and central office personnel to answer requests from 

Congress and for budget, program, and project planning. 

In order to provide both categories of information, the NPS Natural Resource Program 

Center (NRPC) and the I&M Program actively develop and maintain a national-level 

information management framework and suite of applications that use a combination of 

desktop applications and Internet-based systems. 

NRPC staff members work with regional and support office staff to develop extensible 

desktop GIS systems that integrate closely with the database systems. Centralized data 

archiving and distribution capabilities at the NRPC provide for long term data security and 
_________________________________________________________________________ 

18 

storage. NRPC sponsors training courses on data management, I&M techniques, and remote 

sensing to assist I&M data managers with developing and effectively using natural resource 

information. Other programs such as cultural resources and maintenance have their own 

distributed applications that often intersect and also may have broader program application 

and use. 

The principal applications and data repositories developed for the I&M Program and servicewide programs, and referenced throughout this document, are summarized below. 

2.6.1 NatureBib 

NatureBib is the master database for bibliographic references that pertain to park units. It 

also contains citation data from related databases such as NPSpecies, Dataset Catalog, and 

the NPS Data Store. NatureBib currently focuses on park natural resource-related references; 

however, it may eventually be linked to references on cultural resources and other park 

operations. NatureBib comprises both a master, web-based application and interface as well 

as a version in MS Access that can be run locally on a user’s desktop. 

http://www.nature.nps.gov/nrbib

2.6.2 NPSpecies 

NPSpecies is the master database for information on species within park units. The database 

contains data on species that are known or suspected to occur in a park unit, and the 

associated physical or written evidence for the occurrence of the species (i.e., references, 

vouchers, or observations). Taxonomy and nomenclature are based on ITIS, the Integrated 

Taxonomic Information System (http://www.itis.gov/). 

The current version of NPSpecies for each park or network can be downloaded from the 

master web site into a local, MS Access version. The Internet-based version is accessed via 

password-protected log-ins administered by park, network and regional data stewards 

assigned for each park and network. The master database requires that species lists are 

certified by networks before any data will be available to the public. NPSpecies is linked to 

NatureBib for bibliographic references that provide written evidence of a species’ occurrence 

in a park. 

http://science.nature.nps.gov/im/apps/npspp/index.htm 

2.6.3 Dataset Catalog 

Dataset Catalog is an MS Access-based application that provides parks, networks, and 

cooperators a means to document data set holdings. Although not designed as a 

comprehensive metadata tool, the Dataset Catalog is used for creating abbreviated metadata 

about a variety of natural resource data sets. The Dataset Catalog helps parks and networks 

begin to meet Executive Order 12906 mandating federal agencies to document all data 

collected after January 1995. 

http://science.nature.nps.gov/im/apps/datacat/index.htm 

2.6.4 NPStoret 

STORET (STORage and RETrieval) is an interagency water quality database developed and 

supported by the Environmental Protection Agency (EPA) to house local, state, and federal 

water quality data collected in support of managing the nation’s water resources under the 
______________________________________________________________________ 

Chapter 2 – Infrastructure and Systems Architecture 19 

Clean Water Act. STORET is used by NPS as a repository of physical, chemical, biological, 

and other monitoring data collected in and around national park units by park staff, 

contractors, and cooperators. 

NPS operates its own service-wide copy of STORET and makes periodic uploads to the EPA 

STORET National Data Warehouse so that data collected by and for parks will be accessible 

to the public. NPS Director’s Order 77 indicates that the NPS should archive water quality 

data in STORET, and the NPS Water Resources Division (WRD) requires that any data 

collected as part of a funded WRD project be archived in STORET. NPSTORET (also 

known as Water Quality Database Templates) is the NPS master database designed to 

facilitate park-level standardized reporting for STORET. 

The database is still in development; however, metadata, protocols, data dictionaries, and 

reporting capabilities are available through a front-end form. Upon implementation, network 

staff and cooperators will be able to use the MS Access version of NPSTORET either as a 

direct database for data entry and management, or as a means of submitting data for upload 

to STORET by WRD staff. 

http://www.nature.nps.gov/water/infodata.cfm

2.6.5 Natural Resource Database Template 

The Natural Resource Database Template (NRDT) is a set of relational database tables that 

parks and networks can use to develop applications for capturing natural resource inventory 

and monitoring data. NRDT is a core database structure that can be modified and built upon 

by users depending on the components and specific protocols required. Accompanying 

NRDT is the Front-end Application Builder that can be used to build user interfaces, giving 

developers more time for protocol-specific form and report development. 

NRDT includes separate modules for different aspects of monitoring project implementation, 

from sampling design to data analysis and reporting, and includes data management 

components that describe database table structure, data entry forms and quality checking 

routines. Established monitoring protocols, including associated databases that are based on 

NRDT, are available through a web-based protocol clearinghouse (see below). A description 

of the NRDT application, a data dictionary, and examples are located on the NRDT web site. 

http://science.nature.nps.gov/im/apps/template/index.cfm

2.6.6 NPS Data Store 

The NPS Data Store is a key component of the data dissemination strategy employed by the 

NPS servicewide. The web-based search tool links data set metadata to a data server. The 

interface allows customized public or protected searches of natural resource data sets, 

inventory products and GIS data produced by the I&M and Natural Resource GIS Programs. 

Each park or network is able to post and curate its data on the server. 

http://science.nature.nps.gov/nrdata 

2.6.7 Vital Signs Internet Map Services (VSIMS) 

VSIMS provides a consistent way to share and analyze vital signs monitoring data in a 

spatial context. The application allows users to spatially select areas of interest, and to query, 

browse, and download vital signs monitoring data and spatial layers. VSIMS is currently 

under development and is available on the intranet only. Planned capabilities include 
_________________________________________________________________________ 

20 

additional spatial data layers, monitoring data upload and management tools, and additional 

security functions in a publicly-accessible version. 

http://science.nature.nps.gov/nrgis/applications/webmapping/default.aspx 

2.6.8 Natural Resource Monitoring Protocol Clearinghouse 

This is a web-based clearinghouse of protocols that have been developed by the I&M 

networks or other established protocols used in national park units. The database provides a 

summary and download of protocols. 

http://science.nature.nps.gov/im/monitor/protocoldb.cfm 

2.6.9 Natural Resources Monitoring Partnerships (NRMP) 

NRMP is a web-based clearinghouse of monitoring projects and protocols for a diversity of 

state, provincial, federal, university and organizations across Canada and the U.S. The site is 

hosted by the National Biological Information Infrastructure (NBII), a broad, collaborative 

program hosted by the USGS Biological Informatics Office. A number of tools are available 

to search natural resource protocols or to locate a monitoring program. Information from the 

Protocol Clearinghouse (above) is periodically provided to NRMP. For further information 

and to search the biological information database see their web site 

http://www.nbii.gov/portal/community/Communities/Toolkit/Inventory_&_Monitoring/Natur

al_Resources_Monitoring_Partnership

2.6.10 NPS Automated National Catalog System (ANCS+) 

ANCS+ is the official curatorial cataloging system of the NPS and is developed under the 

guidance of the NPS Cultural Resources Program. ANCS+ is run as a stand-alone application 

at the park level, with annual data transfers to the national level. I&M networks do not have 

direct access to ANCS+, which is managed by park curators; however, networks do play an 

important role in contributing data to this system. 

http://www.nps.gov/history/museum/

2.6.11 Research Permit and Reporting System (RPRS) 

Permits are required for anyone, including I&M networks, conducting on-the-ground 

research in a park unit. RPRS is a web-based application used by researchers, park staff, and 

the public for completing and tracking the steps of requesting and issuing research permits, 

and reporting on research accomplishments via the IAR - Investigator's Annual Reports. 

IARs are also a valuable source of information on previous research conducted in parks. 

https://science1.nature.nps.gov/research/ac/ResearchIndex 

2.7 Service-oriented Architecture and the Next Generation of National 

Applications 

In 2006, prompted by the comments and feedback from the users of many of the national 

applications described above, and also based on the recommendations of an outside 

consultant, the NRPC Director issued a policy on NRPC Natural Resource IT Applications 

that established the basis for transitioning these applications to service-oriented architecture 

(SOA). End-users of these applications clearly indicated the need for simplified access and 

streamlined workflow in order to effectively catalog and manage the processes and products 

of natural resource-related efforts. SOA, which is DOI best-practice for application 
______________________________________________________________________ 

Chapter 2 – Infrastructure and Systems Architecture 21 

development, provides an alternative to the existing “silo” architecture, and provides the 

foundation for a modular application design and extensive information sharing. 

2.7.1 Integration of Research Management Applications (IRMA) 

The Integration of Resource Management Applications (IRMA) project was begun in 

October, 2006 in order to implement the 2006 NRPC policy. IRMA is the umbrella project 

that encompasses the planning and implementation of the SOA framework, and the transition 

of existing stand-alone applications into an integrated system of data services. Microsoft’s 

.NET has been selected as the data architecture and SQL Server is the adopted database 

platform. Software development is being implemented exclusively in the C# language. In 

addition, a blade server infrastructure has been established that will allow for failover, 

redundancy, more integrated management, and system health monitoring. A new storage area 

network was also acquired to meet expected significant storage requirements. 

http://nrpcsharepoint/irma/default.aspx

http://www1.nrintra.nps.gov/nrpc_soa/

Transition Plans 

NPSpecies is the first large application to be converted to SOA. This application is being 

redesigned for greater simplicity, efficiency, and speed. It is expected to accommodate any 

number of taxonomic classification systems, and will include a flexible service for managing 

species observation data at a park unit or sub-unit level. The transition is expected to be 

complete in late 2008. The NPS Data Store and NatureBib applications are scheduled for 

conversion after NPSpecies, and will be combined into a single service. This conversion is 

expected to be completed in early 2009. Additional applications will follow, based upon user 

requirements and resources available. 

Implications for I&M Networks 

I&M networks will continue using the existing applications until the phased release of SOA 

services. Data migration to the new services will be automated to the extent possible; 

however, I&M network staff will need to be directly engaged in the conversion process. 

2.8 References and Resources 

Dataset Catalog. Desktop application. 

(http://science.nature.nps.gov/im/apps/datacat/index.htm). Accessed 16 January 2008. 

IBM Corporation. IBM Lotus Sametime. (http://np013denver.nps.gov/). Accessed 16 January 

2008. 

Integrated Taxonomic Information System. Secure online version. (http://www.itis.gov/). 

Accessed 16 January 2008. 

National Biological Information Infrastructure (NBII). Natural Resources Monitoring 

Partnership. 

(http://www.nbii.gov/portal/community/Communities/Toolkit/Inventory_&_Monitori

ng/Natural_Resources_Monitoring_Partnership/). Accessed 16 January 2008. 

National Institute of Standards and Technology. Draft guidance for assessing the security 

controls in federal information systems. NIST Special Publication 800-53A 
_________________________________________________________________________ 

22 

(http://csrc.nist.gov/publications/drafts/800-53A/draft-SP800-53A-fpd-sz.pdf). 

Accessed 23 January 2008. 

National Park Service Automated National Catalog System. Secure online version. 

(http://www.nps.gov/history/museum/). Accessed 16 January 2008. 

National Park Service. Under development. Natural resource protection. Director’s Order 

#77. (http://data2.itc.nps.gov/npspolicy/DOrders.cfm) 

National Park Service. Geographical Information Systems Program, Vital Signs Internet 

Mapping Service. 

(http://science.nature.nps.gov/nrgis/applications/webmapping/default.aspx). Accessed 

16 January 2008. 

National Park Service. Integration of Resource Management Applications (IRMA). 

(http://nrpcsharepoint/irma/default.aspx). Accessed 16 January 2008. 

National Park Service. Integration of Resource Management Applications (IRMA). 

(http://www1.nrintra.nps.gov/nrpc_soa/). Accessed 16 January 2008. [Intranet site] 

National Park Service. 2001. Internet and intranet publishing. Director’s Order #70. 

(http://www.nps.gov/policy/DOrders/DOrder70.html) 

National Park Service, Natural Resource Program Center. 2006. Policy on NRPC natural 

resource IT applications. 

(http://www1.nrintra.nps.gov/nrpc_soa/docs/IT_Policy_26Oct2006.doc) 

 [Establishes policy and guidance for the Integration of Resource Management 

Applications (IRMA) project] 

National Park Service. Natural Resource Program Center SharePoint. (http://nrpcsharepoint). 

Accessed 16 January 2008. 

National Park Service. Natural Resource Program Center SharePoint, I&M networks. 

(http://imnetsharepoint). Accessed 16 January 2008. 

National Park Service. Natural Resources Inventory & Monitoring Program. 

(http://science.nature.nps.gov/im/index.cfm). Accessed 16 January 2008. 

National Park Service. Natural Resources Inventory & Monitoring Program, I&M network 

data management: web authoring. 

(http://www1.nrintra.nps.gov/im/datamgmt/webdev/index.cfm). Accessed 16 January 

2008. 

[Intranet site providing web authoring information for I&M networks] 

National Park Service. Natural Resources Inventory & Monitoring Program, Protocol 

Database. (http://science.nature.nps.gov/im/monitor/protocoldb.cfm). Accessed 16 

January 2008. 
______________________________________________________________________ 

Chapter 2 – Infrastructure and Systems Architecture 23 

National Park Service. Natural Resources Inventory & Monitoring Program's Natural 

Resource Database Template (NRDT). 

(http://science.nature.nps.gov/im/apps/template/index.cfm). Accessed 16 January 

2008. 

National Park Service. [No date] Information technology management. Director’s Order 

#11A. (http://www.nps.gov/policy/DOrders/DO11A-14day.html) 

National Park Service. [No date] Access your national parks: a guide to accessibility 

programs. (http://www.nps.gov/access/). 

[web authoring information to ensure access to electronic information by persons 

with disabilities] 

National Park Service. 2005. Office of the Chief Information Officer (OCIO). OCIO policy 

number: OCIO 2005-0004. (http://classicinside.nps.gov/documents/OCIO%202005-

0004.doc). Accessed 23 January 2008. 

National Park Service. Research Permit and Reporting System. 

(https://science1.nature.nps.gov/research/ac/ResearchIndex). Accessed 16 January 

2008. 

National Park Service. Water Resources Division, information and data. 

(http://www.nature.nps.gov/water/infodata.cfm). Accessed 16 January 2008. 

National Park Service. 2006. Web publishing. Director’s Order #11C (draft). 

(http://www.nps.gov/policy/DOrders/DO-11C.pdf) 

[Under review. Will replace and supersede DO#70 when approved.] 

National Park Service Data Store. Secure online version. 

(http://science.nature.nps.gov/nrdata/). Accessed 16 January 2008. 

National Park Service, Office of the Chief Information Officer. IT policies, standards, 

procedures, and guidance. (http://inside.nps.gov/waso/waso.cfm?prg=308&lv=3)

[List of IT-related policies and procedures] 

National Park Service Species Database. Secure online version. 

(http://science.nature.nps.gov/im/apps/npspp/index.cfm). Accessed 16 January 2008. 

Natural Resource Bibliography. Secure online version. 

(https://science1.nature.nps.gov/naturebib/). Accessed 16 January 2008. 

U.S. Department of Interior. 2005. Guidelines and standards for desktop 

applications.(http://www.doi.gov/ocio/erm/software.html) 

U.S. Department of Interior. 2005-04 (NPS) Local Administration Policy (305.1.1)

(http://inside.nps.gov/waso/custommenu.cfm?lv=3&prg=308&id=2494)
_________________________________________________________________________ 

24 

2.9 Related Network-level SOPs 

 Management of network Internet and intranet web sites 

 Infrastructure organization and maintenance 

 File and directory naming conventions 

 Backup and restore routines for I&M network data 

 Image management 

 Managing audio and video data resources 

 Management, documentation, and dissemination of spatial data 

 SOPs related to network use of NatureBib, NPSpecies, the NPS Data Store, and other 

national applications that may need network-specific documentation 
________________________________________________________________________ 

Chapter 3 – Project Development and Data Management Workflow 25 

CHAPTER 3. Project Management and the Data Life Cycle 

Data management within an I&M network must coordinate the broad phases of short- and 

long-term inventory or monitoring projects, as well as the detailed steps of data acquisition 

and processing. Establishing a structure, sequence, and steps for these phases is needed to 

ensure that all tasks are completed, responsibilities are clear, resources are available, and 

overall workflows are synchronized. 

3.1 Objectives 

The objectives of establishing and maintaining proper project management and a data 

management life cycle are: 

 Ensure that a sequence of steps is applied to all network projects, from project inception 

through to project conclusion 

 Ensure necessary and appropriate participation of staff and cooperators at all stages of 

project development 

 Ensure that all data resulting from projects are consistently processed, reviewed, and 

finalized. 

3.2 Laws and Policies 

The use of standard project management practices is becoming integrated into National Park 

Service information system development. In 2003, the DOI Chief Information Officer issued 

a directive establishing standard project management certification requirements for persons 

managing major and non-major IT investments (U.S. Department of Interior 2003). This 

directive does not currently apply to information systems developed or managed at the I&M 

network level; however, it indicates a recognition that effective project management 

techniques are an essential component to project success. Project management certification 

can be acquired through various sources; NPS recommends that certification be provided by 

the Project Management Institute (PMI). 

3.3 General Standards and Guidelines 

There are two main types of projects handled by I&M networks: 

 Short-term projects: These include individual park research projects, inventories, or pilot 

work done in preparation for long-term monitoring or research. 

 Long-term projects: These include vital-signs monitoring projects central to the I&M 

program, and multi-year research projects and monitoring performed by other park 

programs, agencies and cooperators. Long-term projects often require a higher level of 

documentation, peer review, and program support. 

Both short-term and long-term projects share many work flow characteristics, and both 

generate data products that must be managed and made available. Long-term projects, 

however, have an increased need to adhere to and maintain standards and will require the 

ability to compare data over an extended period of time (decades for long-term monitoring). 
_________________________________________________________________________ 

26 

Data management is a vital component in the development of high-quality scientific data and 

must be considered in every stage of project development. Primary responsibility for these 

activities rests with different individuals according to the different phases of a project (see 

Chapter Four). 

3.4 Stages of Project Development 

Project planning can be broken down into a series of stages, with the number of stages 

dependent upon the methodology used. The Inventory and Monitoring program has 

traditionally used a five-stage method, which is similar to other institutions such as PMI. 

The I&M program’s five project stages are: planning and approval; design and testing; 

implementation; product integration; and evaluation and closure (Figure 3-1). PMI project 

stages are: initiation; planning; executing; controlling; and closeout. Steps taken by both 

methodologies correspond closely, and networks can manage their projects using either 

method. Stages are described below, with the PMI names given in parentheses. 

3.4.1 Planning and Approval (Initiation) 

Most decisions regarding project scope and objectives are made at this stage. 

Funding sources, permits and compliance are also addressed at this time. Primary 

responsibility rests with project leaders and program administrators; however, data 

managers must be informed in order to anticipate data management needs and 

timelines. All contracts, agreements, and permits should include standard language 

that describes the data formats, specifications, metadata requirements, and 

timelines for project deliverables. 

3.4.2 Design and Testing (Planning) 

Details regarding how data will be acquired, processed, documented, analyzed, and reported 

are developed during this stage, as is data discovery. The project leader is responsible for 

developing and testing project methodology, or for modifying existing methods to meet 

project objectives. Project leaders and data managers must work together during this phase in 

order to build and reinforce good data management throughout the project. Data integrity and 

quality can be assured most easily by beginning collaborative development as soon as 

possible after project approval. 

Key data management details to address in this phase include developing documentation of 

project databases (e.g., entity relationship diagrams, data dictionaries, business rules, user 

interface) and formal metadata. Devoting adequate attention to this aspect of a project is the 

single most important step in assuring the quality, integrity and usability of the resulting data. 

Although post-hoc changes will inevitably be required, careful design can minimize database 

rework. 
________________________________________________________________________ 

Chapter 3 – Project Development and Data Management Workflow 27 

 

Figure 3-1. Data management steps during the five stages of project development. Key data 

management activities are in bold type. 

Long-term 

monitoring and 

other multi-year 

projects 

Revisions to 

protocols and 

databases 

Administrative 

reporting & 

work plan 

Project Start 

Planning and 

approval 

Design and 

testing 

Implementation

Preparation 

Data 

acquisition & 

processing 

Product 

development

, delivery & 

review 

Product 

integration 

Evaluation and 

closure 

Project conclusion 

 Yes 

 No 

Background review of related, existing information 

Identify measurable objectives and target populations 

Develop proposal and budget, solicit and secure funding 

Complete contracts/agreements, permits, compliance* 

Develop study plan 

Identify project deliverables 

Develop methodology or adapt existing methods* 

Define SOPSs and guidelines 

Create/revise data sheets and data dictionaries 

Complete Data design and modifications 

Initiate work development 

Identify destinations for deliverables 

Conduct Peer review

Logistics, planning, hiring, contracting, and training 

Installation of equipment and monitoring protocols 

Equipment purchase and maintenance 

Data collection, acquisition of external data sets 

Data entry, processing, quality assurance 

Data validation, and certification 

Summarization, analysis, and map productions 

Interpretation and reporting 

Metadata development 

Product review and revision 

Finalize and distribute metadata & data products

Integrate project data with national databases 

Catalog products 

Archive and store digital files and other products

Evaluate how well project met objectives and what 

modifications need to be made to methods, 

procedures, data design, etc. 

Sign off - project requirements have been met and 

deliverables are complete and available

Data Management Activities 

Changes 

needed? 

* Determination of permit and compliance requirements often requires detailed knowledge of project 

methods, which are often not fully developed until after the planning and approval stage; therefore, 

methods development and compliance is an iterative process. 
_________________________________________________________________________ 

28 

3.4.3 Implementation (Executing and Controlling) 

During this phase data are acquired, processed, error-checked and further documented, and 

products such as reports, maps, GIS themes, and other products are developed. The project 

leader oversees all aspects of implementation, including logistics planning, contracting, 

training, equipment procurement, data acquisition, documentation, report preparation and 

final delivery. Data management staff function primarily as facilitators, providing training 

and support for database applications, GIS, GPS and other data processing applications; 

facilitation of data summarization, validation and analysis; and assistance with the technical 

aspects of documentation and product development. The specific roles of data management 

staff will depend primarily on the technical capabilities of the project staff. As much as 

possible, these roles should be determined in advance of implementation. Toward the 

conclusion of this phase, project staff members work to develop and finalize the deliverables 

that were identified in the project planning documents (e.g., protocol, study plan, contracts, 

agreements, permits). 

3.4.4 Product Integration and Distribution (Executing and Controlling) 

Data are certified by the project leader and merged from any working databases to a final 

database. Metadata are finalized, and products are posted in national repositories or otherwise 

distributed in the desired formats to the intended audience. This stage may also include 

upload to I&M national-level databases (e.g., cataloging in NatureBib, updating NPSpecies, 

posting metadata and associated files to the NPS Data Store). These updates allow the 

information from the project to be searchable and available to others service-wide. Certain 

projects may also have additional integration needs, such as when working collaboratively 

with other agencies. 

In general, all raw and derived data products, metadata, reports and other documentation 

should be delivered to the data steward assigned to the project. Administrative records should 

be delivered to appropriate park and I&M network staff as specified. All project deliverables 

should be distributed according to specifications, which should be stipulated in all protocols, 

contracts, agreements, and permits. Products that do not meet program requirements should 

be returned for revision. 

3.4.5 Evaluation and Closure (Closing) 

Records are updated to reflect the status of the project and its associated deliverables in a 

network project tracking application. For long-term monitoring and other cyclic projects, this 

phase occurs at the end of each field season, and leads to an annual review of the project. For 

short term (non-cyclic) projects, this phase represents the completion of the project. After 

products are catalogued and made available, program administrators, project leaders, and 

data managers should work together to assess how well the project met its objectives, and to 

determine what might be done to improve various aspects of the methodology, 

implementation, and formats of the resulting information. For monitoring protocols, careful 

documentation of all changes is required. Changes to methods, standard operating 

procedures, and other procedures are maintained in a tracking table associated with each 

document. Major revisions may require additional peer review. 
________________________________________________________________________ 

Chapter 3 – Project Development and Data Management Workflow 29 

3.5 The Data Life Cycle 

Data take on different forms during various phases of a project, and are maintained in 

different places as they are acquired, processed, documented, analyzed, reported, and 

distributed. This is referred to as the "data life cycle" (Figure 3-2), which is characterized by 

the series of events listed as follows: 

Figure 3-2. The data life cycle. 

1. Acquire data – Data are acquired in digital or analog form. Digital data can be recorded 

on handheld computers and PDAs, tablets, data loggers, or laptop computers. Analog data 

are entered on field data sheets. Acquisition can include both programmatic and nonprogrammatic data. 

2. Archive raw data – Copies of all raw data files are archived intact. Digital files are copied 

to the digital library; hard copy forms are either scanned and placed in the digital library 
_________________________________________________________________________ 

30 

or are copied and placed in the archives. Note: Archiving or scanning of hard copy data 

forms may occur at the end of a season as a means of retaining all marks and edits made 

during the verification and validation steps. 

3. Enter/import data – hand-recorded data are keyed in and digital data files are uploaded to 

the working database. 

4. Verify, process, and validate – Verify that raw data have been accurately transcribed. 

Data are processed to remove missing values and other flaws; and data are validated 

through visual inspection and queries to capture missing data, out-of-range values, logical 

errors, and violations of pre-defined business rules (see step 2, above). 

5. Documentation and certification – Develop or update project metadata and certify the 

data set. Certification is a confirmation by the project leader that the data have passed all 

quality assurance requirements and are complete and documented. After certification, all 

data and metadata are ready to be posted and delivered. 

6. Upload data – Certified data are uploaded from the working database to the master 

project database. This step may not be required for short-term projects where there is no 

need to distinguish working data for the current season from the full set of certified 

project data. 

7. Archive versioned data set – A project data certification form is completed and filed with 

the data set. Copies of certified data and metadata should be stored in the ntwork’s digital 

library. This can be accomplished by storing a compressed copy of the working database 

or by exporting data to a more software-independent format (e.g., ASCII text, XML). 

8. Disseminate data and update national databases– Certified data and metadata, and 

digital image products are posted to national repositories (i.e.,NPS Data Store) to make 

them more broadly available to others. National databases, including NPSpecies, 

NPSTORET, and ANCS+ are updated with data obtained from certified data sets. 

9. Reporting and analysis – Certified data are used to generate information products, 

analyses, and reports, including semi-automated annual summary reports for monitoring 

projects. Depending on project needs, data might be exported for analysis or summarized 

within the database. 

10. Distribute information products – Information products such as reports, maps, and 

checklists are disseminated to the public through the national and network web sites and 

cataloged in NatureBib. 

11. Share data and information – Data, metadata, reports and other information products can 

be shared in a variety of ways – by FTP or mailing in response to specific requests, or by 

providing direct access to project records to park staff and cooperators. 

12. Track changes – All subsequent changes to certified data are documented in an edit log, 

which accompanies project data and metadata upon distribution. Significant edits will 

trigger reposting of the data and products to national databases and repositories. 
________________________________________________________________________ 

Chapter 3 – Project Development and Data Management Workflow 31 

13. Store products – Reports and other data products are stored according to format and 

likely demand, either in the digital library, on off-line media, or in the document archives. 

14. Catalog project products – Catalog products and all information associated with a 

project, including results of analyses and paths of dissemination. Project tracking 

databases can be useful tools for this purpose. 

For long-term projects, this sequence of events occurs in an iterative fashion, repeating at the 

end of each field season or other logical data collection and reporting period. Conversely, this 

sequence is followed only once for short-term projects. For projects spanning multiple years, 

decision points include whether or not a separate working database is needed, and the extent 

to which product development and delivery is repeated. 

3.6 References and Resources 

NPS Information Systems Project Management Community 

(http://inside.nps.gov/waso/custommenu.cfm?lv=3&prg=737&id=3488) 

Project Management Institute (http://www.pmi.org/Pages/default.aspx) 

U.S. Department of the Interior. 2003. Project management certification requirements for 

managing information technology investments. Office of the Secretary. 

(http://inside.nps.gov/waso/custommenu.cfm?lv=3&prg=308&id=2141) 

3.7 Related Network-level SOPs 

 Checklist for initiating a new project 

 I&M network project management 

 Project specifications and deliverables 

 Guidelines for protocol development 

 Data processing and data lifecycle workflow 

 Procedures for certifying project data 

 Guidelines for project and budget tracking 
_________________________________________________________________________ 

32 

 
________________________________________________________________________ 

Chapter 4 - Data Management Roles and Responsibilities 33

CHAPTER 4. Data Management Roles and 

Responsibilities 

Data management is about individuals and organizations as much as it is about information 

technology, database practices, and applications. All staff participating in an I&M network 

project have a role in data stewardship, and project data sets and products reflect all who 

have contributed. In order to meet the data management goals and standards developed by 

the National Park Service and the I&M Program, all staff must understand their associated 

roles and responsibilities. 

4.1 Objectives 

The objectives of delineating data management roles and responsibilities are: 

 clearly define roles associated with functions 

 establish data ownership throughout all phases of a project 

 instill data accountability 

 ensure that adequate, agreed-upon data quality and metadata metrics are maintained on a 

continuous basis. 

4.2 Laws and Policies 

There are no laws or NPS policies governing the establishment of roles and responsibilities 

with respect to data management. Documenting data-related roles and responsibilities is, 

however, a best practice: it notifies all persons involved with a project or I&M network of 

their role in ensuring that data collected, managed, and disseminated are of the highest 

quality. 

4.3 General Standards and Guidelines 

Individuals from different disciplines and backgrounds must collaborate to ensure that data 

are collected using appropriate methods, and that resulting data sets, reports, maps, models, 

and other information products are credible, representative, and accessible for current and 

future needs. 

The principal roles assumed for the production, analysis, management, and end use of data 

will vary based on the I&M network and the nature of the project. For a small staff, many 

activities might be accomplished by a single individual. For large programs, a much higher 

degree of specialization is typically required. Table 4-1 summarizes general types of data 

management activities and the roles typically associated with them. Although each position is 

associated with only one category according to overriding responsibilities, many positions 

contribute to multiple categories. 
_________________________________________________________________________ 

34 

Table 4-1. Categories of data stewardship. 

Stewardship 

Activity 

Description of Activities Principal Roles 

Production Creating data or information from any original or 

derived source. This includes recording locations, 

images, measurements, and observations in the 

field, digitizing source maps, keying in data from a 

hardcopy source, converting existing data 

sources, image processing, and preparing and 

delivering informative products, such as summary 

tables, maps, charts, and reports. 

 Project Crew Leader 

 Project Crew Member 

 Data/GIS Specialist or 

Technician 

Analysis Using data to predict, qualify, and quantify 

ecosystem elements, structure, and function as 

part of the effort to understand these components, 

address monitoring objectives, and inform park 

and ecosystem management. 

 Ecologists 

 Resource Specialists 

Management Preparing and executing policies, procedures, and 

activities that keep data and information resources 

organized, available, useful, compliant, and safe. 

 Project Leader 

 Data Manager 

 GIS Manager 

 IT Specialist 

 Database Manager 

 National-level Data 

Managers 

End Use Obtaining and applying available information to 

develop knowledge that contributes to 

understanding and managing park resources. 

 Park Managers 

 Superintendents 

 Network Coordinators 

 Others 

4.4 Specific Data Management Roles and Responsibilities 

4.4.1 Data Managers 

The I&M network data manager works with national I&M Program data management staff 

and regional resource information management personnel to maintain a high level of 

involvement in service-wide and regional databases and data management policy. The 

network data manager works locally with network personnel, park staff, and cooperators to 

promote and develop workable standards and procedures that result in the integration and 

availability of data sets. 

Key contacts for the network data manager include park and/or regional GIS and data 

managers, and the project leaders for each monitoring or inventory project. Consistent and 

productive communication among these staff leads to common understanding and better 

synchronization of network and park data management activities. Networks can benefit 

greatly by a close working relationship with park staff, including personal visits, joint 

meetings and training sessions, and the meetings and work of the network’s Technical 

Steering Committee and/or Board of Directors. Involvement and input from park scientists 

and resource information management staff is essential. 
________________________________________________________________________ 

Chapter 4 - Data Management Roles and Responsibilities 35

Data managers will: 

 Develop and maintain the infrastructure for metadata creation, project documentation and 

project data management 

 Create and maintain project databases in accordance with best practices and current 

program standards 

 Provide training in the theory and practice of data management tailored to the needs of 

project personnel 

 Develop ways to improve the accessibility and usability of digital data 

 Establish and implement procedures to protect sensitive data according to project needs 

 Collaborate with GIS specialists to integrate tabular data with geospatial data in a GIS 

system in a manner that meets project objectives.

Data managers will also work closely with the project leader to: 

 Define the scope of the project data and create data structures that meets project needs 

 Become familiar with how the data are collected, handled, and used 

 Review quality control and quality assurance aspects of project protocols and standard 

procedure documentation 

 Identify business rule constraints that can be built into the database structure to facilitate 

quality control, such as required fields, data domains, pick-lists and conditional validation 

rules 

 Create user interfaces that streamline the process of data entry, review, validation, and 

summarization that is consistent with the capabilities of the project staff 

 Develop automated database procedures to improve the efficiency of the data 

summarization and reporting process 

 Ensure that project documentation is complete, complies with metadata requirements, and 

enhances the interpretability and longevity of the project data 

 Ensure regular archiving of project materials

 Inform project staff of changes and advances in data management practices.

The amount of collateral duties a data manager may have to perform varies from network to 

network depending on the physical location, budget, and overall resources available to a 

network. While some of these other duties cannot be avoided it should be noted that data 

managers are not responsible for: 

 Park GIS and database solutions outside of the scope of the I&M Program. Data 

managers are encouraged to assist parks when skills and expertise are required, but 

should not be solely responsible for implementing projects at the park level 

 Park IT network administration and support, including hardware and software issues 

 General data entry or keying data from field forms 

 I&M Program administrative support 

4.4.2 GIS Specialists 

GIS specialists manage spatial data themes associated with I&M network inventory and 

monitoring projects, as well as other spatial data related to natural resource inventories and 

vital signs monitoring. GIS specialists maintain standards for geographic data and are 

responsible for sharing, integrating, and disseminating GIS data as needed. 
_________________________________________________________________________ 

36 

The GIS specialists will work with project leaders to: 

 Determine the GIS data and analysis needs for the project 

 Develop procedures for field collection of spatial data including the use of GPS and other 

spatial data collection techniques 

 Display, analyze, and create maps from spatial data to meet project objectives 

 Properly document data in compliance with spatial metadata standards 

GIS specialists will work directly with data managers to: 

 Design databases and other applications for the network 

 Create relationships between GIS and non-spatial data 

 Create database and GIS applications to facilitate the integration and analysis of both 

spatial and non-spatial data 

 Establish and implement procedures to protect sensitive spatial data according to project 

needs 

 Develop and maintain an infrastructure for metadata creation and maintenance 

 Ensure that project metadata are created and comply with national and agency standards

4.4.3 Project Leaders 

Since the data management aspects of every inventory or monitoring project normally require 

the expertise and involvement of several persons over a period of months or years, it makes 

sense that one person is charged with keeping track of the objectives, requirements, and 

progress for each project. This project leader is usually a resource management specialist or 

scientist with training, experience, or authoritative knowledge in the field of science related 

to the project. 

The project leader is responsible for data quality during all phases of the project, including 

collecting, entering, handling, reviewing, summarizing, and reporting data. Developing 

project documentation and metadata are crucial elements of the project leader’s role. The 

overlap between project and data management responsibilities is illustrated in Figure 4-1. 
________________________________________________________________________ 

Chapter 4 - Data Management Roles and Responsibilities 37

Figure 4-1. The overlap between data management responsibilities of the project leader and 

data manager. 

Specifically, a project leader is responsible for: 

 project documentation that describes the who, what, where, when, why, and how of a 

project 

 documentation and implementation of standard procedures for field data collection and 

data handling 

 quality assurance and quality control measures, which include the supervision and 

certification of all field operations, staff training, equipment calibration, species 

identification, data collection, data entry, verification, and validation 

 maintenance of concise explanatory documentation of all deviations from standard 

procedures 

 detailed documentation for each field data collection period 

 maintenance of hard copies of data forms and archiving of original data forms 

 scheduling of regular project milestones such as data collection periods, data processing 

target dates, and reporting deadlines 

 regular summary reports, periodic trend analyses of data, and their public availability 

 acting as the main point of contact concerning data content

The project leader will also work closely with the data manager to: 

 develop quality assurance and quality control procedures specific to project operations 

 identify training needs for staff related to data management philosophy, database 

software use, and quality control procedures 

 coordinate changes to the field data forms and the user interface for the project database 

 document and maintain master data 

 identify sensitive information that requires special consideration prior to distribution 

 manage the archival process to ensure regular archiving of project documentation, 

original field data, databases, reports and summaries, and other products from the project 

 define the process of how project data will be transformed from raw data into meaningful 

information 

 create data summary procedures to automate and standardize these transformations 

 identify and prioritize legacy data for conversion and convert priority data sets to a 

modern format 

 increase the interpretability and accessibility of existing natural resource information 

4.4.4 Shared Responsibilities 

Keeping track of data from the time of acquisition until archiving is the shared responsibility 

of everyone involved with data–whether producer, analyst, manager, or end user. Proper data 

stewardship is a principle of mutual accountability rather than one job for one individual. 

Data stewardship requires that persons involved in a projects activities learn and understand 

the expectations for continuous information management. This is equally important for I&M 

network staff, park employees, and contractors or cooperators. All project participants should 

receive training, briefings, materials, and additional regular communication about data 

stewardship from supervisors, project leaders, and data managers. Thus, everyone 
_________________________________________________________________________ 

38 

understands how their efforts relate to park and network management objectives, National 

Park Service and Department of Interior policies, and other federal government requirements. 

I&M project leaders must recognize and understand information management issues and 

requirements. In particular, well-trained field crews, and an ongoing plan for improving their 

technical skills (e.g., GPS, data quality assurance/quality control) will significantly improve 

all aspects of data processing. 

Careful documentation of data sets, data sources, and the methodology by which the data 

were collected or acquired is a key responsibility shared by all project participants. 

Documentation establishes the basis for the appropriate use of the data in resulting analysis 

and products, both in the short-term and long-term. Network monitoring protocols contain 

key elements of data documentation. Careful documentation provides the end user with 

consistent data of known quality and that documentation requires the coordinated effort of all 

who are involved with a project.

4.5 References and Resources 

4.6 Related Network-level SOPs 

 Network data management roles and responsibilities 

 Project roles and responsibilities
________________________________________________________________________ 

Chapter 5 - Databases 39

CHAPTER 5. Databases 

The quantity and complexity of data acquired as part of I&M network inventory and vital 

signs monitoring projects requires a well-planned and consistent approach to database design, 

development, and management. Databases are the cornerstone of an I&M network, and are 

the primary repositories of data from long-term studies that will need to be accessible and 

applicable for decades to come. In addition, network databases must accommodate a wide 

diversity of data types, enforce data integrity, support a variety of queries and output, and 

help substantiate resource management decisions. 

5.1 Objectives 

The objectives of effective database design, development, and management within I&M 

networks are: 

 Ensure the long-term stability, security, and accessibility of data 

 Encourage common practices, standards, and sharing of database development efforts 

among networks 

 Encourage data exchange and multidisciplinary applications of data 

 Ensure databases are designed and built using NPS- and industry-accepted best practices 

5.2 Laws and Policies 

There are no NPS-wide standards on database design or management. The I&M Program has 

established the Natural Resource Database Template as the preferred structure for databases 

designed for vital signs monitoring data. 

5.3 General Standards and Guidelines 

The I&M Program has developed a series of recommendations related to database design that 

include: 

 Natural Resource Database Template (NRDT) data structure and standards 

(http://science.nature.nps.gov/im/apps/template/index.cfm) 

 Guidelines for long-term monitoring protocols (Oakley et al. 2003) 

In addition, I&M networks continue to develop and refine database-related standards based 

on practical experience. Many of these standards are posted on the I&M Data Management 

intranet site (http://www1.nrintra.nps.gov/im/datamgmt/) 

5.3.1 Natural Resource Database Template 

The Natural Resource Database Template (NRDT) has been developed by the Inventory and 

Monitoring Program as its database standard (National Park Service 2007). NRDT is a core 

database structure that can be modified to accommodate specific data needs and sampling 

protocols. NRDT: 

 Provides both a data interchange standard and a standard MS Access database core 

that allows flexibility in application design 

 Serves as a starting point for application development that can be extended as 

necessary to accommodate any inventory or monitoring field sampling protocol 
_________________________________________________________________________ 

40 

 Standardizes location and observation data to facilitate the integration of data sets 

 Acts as a design platform for developing database applications in MS Access 

allowing users to enter, edit, display, summarize, and generate reports for inventory 

or monitoring data sets 

 Integrates with other I&M data management systems and data standards including 

Geographic Information System (GIS) tools and data, and the NPS Metadata Profile 

 Is accompanied by an MS Access Front-end Application Builder that can be used to 

create a user-interface. This includes many built-in utilities such as table linking, 

backups, compaction, and lookup table management. 

Monitoring protocols that include a NRDT-based application should be posted on the webbased monitoring protocol clearinghouse. Users can download a written monitoring protocol 

from the clearinghouse, and contact the network data managear to obtain the corresponding 

database objects such as tables, queries, forms and reports. The fact that a similar NRDT 

structure is used by many simplifies the sharing and exchange of work. 

5.3.2 Project Database Standards 

In addition to the NRDT structure described above, project database standards are necessary 

for ensuring compatibility among I&M data sets, which provides the groundwork for data 

sets to be aggregated or summarized. Well-thought-out standards also encourage sound 

database design. The following considerations should be addressed when designing project 

databases: 

 Standardized database object naming: objects such as tables, fields, queries, forms, 

and reports should be named according to conventions adopted in an SOP 

 Links to central databases: links to data tables that reside in central databases prevent 

storing redundant information in multiple project databases. These tables typically 

contain information that is complex to maintain and is applicable to many projects. 

Examples include: master version tables for vital signs projects; network-wide species 

and vegetation data; data user logs; and data edit logs. 

 Standardized look-up or enumeration tables: many data tables are used repeatedly in 

project databases. Standardized versions of these tables should be stored at a central 

location so they can be easily copied or linked to project databases. 

 Project-specific fields and tables: the remainder of database objects can be 

considered project-specific, although there will typically be some overlap among 

projects. I&M networks are encouraged to work with other networks performing 

similar projects in order to identify any standards or commonalities that might be 

shared. 

Levels of Database Standards 

Links to central databases and the use of common lookup and/or enumeration tables 

represent the first level of data standards because they are consistent among data sets. A 

second level of standards is established by the core template fields and tables, which are 

standardized where possible (however, project-specific objectives could lead to variation 

among projects). The third level of standards is applied most flexibly to accommodate the 

range of needs and possibilities for each project, yet always with compatibility and integrity 
________________________________________________________________________ 

Chapter 5 - Databases 41

in mind. Figure 5-1 illustrates these levels, with central data providing the foundation upon 

which levels two and three are built. 

Figure 5-1. Different levels of data standards and their corresponding degree of variability. 

Examples of standard attributes and values to be developed include: park unit codes, place 

names, watershed codes, species identifiers, and vegetation or land type classifications. To 

the extent possible, networks should collaborate among themselves to develop and use shared 

look-up tables for data consistency and potential multi-network data sharing. 

5.4 Database Planning and Workflow 

Successful databases are the result of the thoughtful use of technology to successfully meet 

user requirements. These requirements should be defined precisely before beginning any 

application development. Database planning and development should be an iterative process 

among data management staff and users, with interim designs and products available for 

review, comment, and modification as needed. 

5.4.1 Application Development Process 

Figure 5-2 presents a sequence of stages in the application development process. 

Products developed early in the project life cycle (e.g., study plans, sampling protocols and 

standard operating procedures) are essential background for database developers. Stages one 

through three are accomplished primarily by the project principal investigators. The project is 

proposed, approved,and protocols and standard operating procedures are developed. These 

materials will be the foundation for database requirements in later stages. 

Stage Four consists of an initial data management consultation where background materials 

that will define the application are assembled and organized. Monitoring protocols are 

critical since they contain much of the intellectual work that define what information will be 

collected, who will collect it, and what it will be used for. At the initial consultation the 

investigator should be prepared to provide: 
_________________________________________________________________________ 

42 

 Project Narrative and draft SOPs 

 List of stakeholders, end users, and their requirements 

 Field forms (if using) 

 Data collection flow diagram 

 Examples (even if hand drawn) of how the information will be analyzed and reported 

 List of software or applications that need to be compatible, such as statistical software or 

export/import formats for other agencies 

 Sample data for testing 

 Estimation of number of records per year. 

Figure 5-2. Monitoring database application development process. Stages shown in blue 

represent tasks that require specific input from scientists to guide the database development 

process. 

A database planning checklist is helpful at this stage. Such a checklist should include: 

 A list of stakeholders and their requirements 

 A work and data collection flow chart 

 Specifications for 

12. Quality Control 

1. Project Initiation 

2. Write Study Plan/Proposal 

and obtain approval

3. Write Sampling Protocols 

5. Model Data/Work flow chart 

7. Build Database and Data 

Application 

8. Test Database 

11. Collect Data 

9.Changes 

Needed? 

Revision 

13. Certification 

4. Initial Data Management 

Consultation to discuss scope 

of project (filling out this 

document) 

6. Review 

with PI, 

Changes

Needed? 

Revision 

10. Write Documentation 
________________________________________________________________________ 

Chapter 5 - Databases 43

o The life span of the project 

o The location where data will be collected 

o Time of data collection 

o Manner of data collection 

o Field computing requirements and risks 

o Database versioning requirements 

o Data type (tabular, spatial, etc.) 

 Preliminary data model (what entities are of interest; what are their attributes?) 

 Integration with other software, hardware 

 Integration with other stakeholder agencies or organizations 

 GPS/GIS requirements 

 Milestones for tracking project progress 

Stages five and six involve modeling the project’s data. This must be an iterative process 

among data managers, database developers and project leaders. In these stages, the model is 

developed, reviewed and revised until it meets all requirements. It is least expensive and 

most efficient to resolve any issues with the data application at this stage, rather than after the 

database is in development. 

Database and application development can proceed once the data model is mature. Stages 

seven through nine represent another iterative cycle where stakeholders must participate in 

the application’s tuning and refinement. Documentation (Stage 10) should be fairly well 

defined from the data model and supporting documentation. Instructions on the use of the 

database should be included in the project’s data management protocol as well as a help file 

and user guide. This step is particularly important for monitoring databases where it is 

assumed that many persons unfamiliar with the database will be using it during each 

sampling season. 

Stages 11 through 13 represent database implementation, at which point it undergoes an 

established series of quality assurance and certification steps. 

While databases will reach a certain level of stability, changes and updates will be ongoing as 

field methods are revised, and technology and platforms evolve. 

5.5 Data Modeling 

The majority of the work involved in building databases occurs long before using any 

database software. Successful database planning takes the form of a thorough user 

requirements analysis, followed by data modeling. 

Understanding user requirements is the first planning step. Databases must be designed to 

meet user needs, ranging from data acquisition through data entry, reporting, and long-term 

analysis. Data modeling is the methodology that identifies the path to meet user 

requirements. Data models may be as simple as a written document or drawing, or may be 

complex and constructed with the aid of software engineering tools. 

5.5.1 Model Development 

Four elements are required to develop the data models: 

Project staff need to participate in the model development. Discussions may begin among a 

few, with later review from a larger group or start with a large group working towards the 
_________________________________________________________________________ 

44 

specifics with a smaller group. Affected people may include the network coordinator, 

scientists, partners, field crews, biometricians, and data managers. 

Protocols for the vital sign will provide the greatest substance to the models. The protocols 

provide the goals, objectives, sampling designs,methods, standards, analyses, and reporting 

requirements. Development of these documents provides an opportunity for project leaders 

and data managers to identify suitable data model requirements. The outcome should be a 

clear, precise description of the framework for a functional monitoring database. 

Reference materials such as field forms, drawings, mock-up reports, and classification 

schemes to be used will play a significant role in the data models. 

Frequent interactions among the project leader, the data manager, and others will be needed 

to develop successful data models. Detailed review of the protocols and reference materials 

will articulate the entities, relationships, and flow of information. Data modeling should be 

iterative and interactive. The following broad questions are a good starting point: 

 What are the database objectives? 

 How will the database assist in meeting those objectives? 

 Who are the stakeholders in the database? Who has a vested interest in its success? 

 Who will use the database and what tasks do those individuals need the database to 

accomplish? 

 What information will the database hold? 

 What are the most atomic bits of information the database will hold and what are their 

characteristics? 

 Will the database need to interact with other databases and applications? What 

accommodations will be needed? 

5.5.2 Conceptual Data Models 

Conceptual data models are constructed to graphically portray the processes specifically 

related to the implementation phase of a project – especially those that involve data 

acquisition, processing, quality assurance/quality control, and data reduction. These 

conceptual models are software-independent and free of database details, and instead focus 

upon capturing all of the information needed to accurately express the project data design. 

Conceptual data models are often created as the precursor to logical data models (LDMs), 

and may be discarded after the LDM is complete, or kept as alternatives to LDMs, with less 

complex projects. 

Conceptual data models should contain the following: 

 A short description in layman’s terms of what is going to happen. Include key 

information to help put the database in perspective, such as environmental conditions 

while collecting, skill level of staff, etc. 

 A flow diagram of procedures, what information is needed and when, and what 

information is being collected or produced and when 

 Descriptions or mock-up illustrations of how the data should be presented. 
________________________________________________________________________ 

Chapter 5 - Databases 45

5.5.3 Logical Data Models 

A logical data model is an abstract representation of a set of data entities and their 

relationship, usually including their key attributes. The logical data model is intended to 

facilitate analysis of the function of the data design, and is not intended to be a full 

representation of the physical database. It is typically produced early in system design, and it 

is frequently a precursor to the physical data model that documents the actual implementation 

of the database. Logical data models are made up of four main components: 

Data entities are distinct features, events, observations, and objects that are the building 

blocks of a data set, such as: 

 Sample sites 

 Sampling events 

 Sampling units (transects, plots, etc.) 

 Watersheds 

 Species 

 Habitat types 

 Species observations 

 Tissue specimens 

Entity attributes are properties and rules of data entities, such as: 

 Sample sites have dimensions and a geographic position 

 Vegetation transects are 100 meters long 

 Temperature readings are recorded in Celsius to the nearest tenth degree 

 Elevation is recorded to the nearest foot, and cannot exceed 9,000 feet 

 Species abundance is recorded in terms of projected horizontal cover of all aboveground 

parts, as estimated by trained observers. Percent cover is estimated to the nearest whole 

number, ranging from 0 to 100%. 

 The degree to which vegetation obstructs the field of view around animal groups is 

classified in three categories: high (>75%), medium (25-75%) and low (<25%) 

Logical relationships illustrate how data entities are logically related: 

 Each site will be visited numerous times 

 Each sampling event might have zero or numerous species observations 

 Each species can only be observed once per sampling event 

 Every sample must use one of three known sample methods 

 Every time a water sample is collected, temperature, pH and dissolved oxygen must also 

be measured 

Structural hierarchies demonstrate the structure and order of relationships among data 

entities, which can be determined once the logical relationships are known: 

 Site locations 

 Sampling event 

 Species observations 

 Water samples, temperature, pH, dissolved oxygen 

 Views – how the data will be viewed or what operations of the data will be performed 

 Summary list of bird species per park 
_________________________________________________________________________ 

46 

 Monthly average air temperature, wind direction, and precipitation 

5.5.4 Physical Data Models 

The physical data model is used to design the actual database, depicting data tables, fields 

and definitions, and relationships between tables. Though the logical and physical data 

models are similar, the logical data model only provides enough detail to communicate the 

information to be stored in the database. The physical data model provides very specific 

details and definitions, such as primary keys and field types. 

5.6 Other Database Considerations 

5.6.1 Data Normalization 

Normalization is the process of designing database tables to ensure that data elements in one 

table are not repeated in other tables. This ensures that data are stored in one location only, 

enforces data integrity, and guards against logical inconsistency in the data. There are six 

levels of normalization (normal forms); however, design beyond the third normal form would 

likely not be required. 

5.6.2 The Triple Constraint (Scope, Time, Resources) 

Building an effective database is a complex process that requires a considerable commitment 

of resources. Database development often needs to balance competing demands and tradeoffs for quality, cost (resources), and time. In the first illustration in Figure 5-3, increasing or 

decreasing one point on the triangle will affect the other two points. Another perspective on 

this is in the second illustration: attaining two points on the triangle usually means sacrificing 

the remaining point. The concept of the triple constraint can be a helpful illustration when 

working with project staff, and can help clarify priorities and limitations. 

Figure 5-3. The triple constraint triangles 

5.6.3 Build, Buy or Adapt 

For some data management functions within an I&M network there may be options available 

such as building a new database, buying commercial off-the-shelf software (COTS), or 

adapting a database or system that has been built elsewhere. For most vital-signs monitoring 

projects, data managers will either be using an NRDT core as a starting point, or will be 

adapting a similar database built by another I&M network. Data managers should investigate 

options for COTS for specific functions such as photo management, database modeling, or 

project management. 

Cost 

Scope Time Good Fast

Cheap
________________________________________________________________________ 

Chapter 5 - Databases 47

5.6.4 Database Software 

All databases have a software mechanism for storing structured data and a language for 

querying and manipulating the underlying information. While MS Access has been the 

primary database application software used by I&M networks, it is proving to be limiting for 

networks needing a larger central data repository or with many distributed concurrent users. 

Client-server or n-tier database architectures are better options to securely store and serve 

data, can more easily handle concurrent use, transactions, triggers, and database permissions 

and constraints. Microsoft SQL Server Express Edition is an option that some networks are 

choosing as an alternative to MS Access. Other options would be Microsoft SQL Server 

Workgroup or Standard editions. Most NRPC applications, including components of the 

IRMA project, are moving towards SQL Server as the primary database platform (as opposed 

to the competing Oracle products), which will increase the ability of NRPC staff to provide 

technical assistance to networks. 

5.7 References and Resources 

National Park Service. Natural Resources Inventory & Monitoring Program, data 

management intranet. (http://www1.nrintra.nps.gov/im/datamgmt/). Accessed 16 

January 2008. 

National Park Service. 2007. Natural Resources Inventory & Monitoring Program, natural 

resource database template [documentation and MS Access database]. 

(http://science.nature.nps.gov/im/apps/template/index.cfm) 

Oakley, K., L. Thomas, S. Fancy. 2003. Guidelines for long-term monitoring protocols. 

Wildlife Society Bulletin 31(4): 1000-1003. 

5.8 Related Network-specific SOPs 

 Checklist for initiating a new project 

 Database application specifications 

 Database object naming conventions 

 Database documentation and data dictionary guidance 
_________________________________________________________________________ 

48 
________________________________________________________________________ 

Chapter 6 - Data Acquisition, Processing, and Reporting 49

CHAPTER 6. Data Acquisition, Processing, and Reporting 

Interdisciplinary or multi-scale natural resource programs and projects increasingly rely on 

data gathered from multiple sources. This chapter describes the general steps involved with 

acquiring, processing, and reporting data to meet standards established by the NPS I&M 

Program, although these steps could apply to other NPS park units or programs. Data 

acquisition also encompasses physical objects (e.g., photographs, voucher specimens), which 

are often collected as part of resource management, inventory and monitoring, and other 

research projects. 

6.1 Objectives 

Acquiring, processing, and reporting on natural resource-related data are core responsibilities 

of I&M networks. To effectively meet these responsibilities networks must: 

 Identify, evaluate, and acquire, through a variety of sources, data needed by networks 

to properly carry out inventory or vital signs monitoring projects within parks 

 Determine the most reliable and efficient means or tools for collecting data 

 Establish routines and procedures for data processing 

 Identify and meet the information needs of a broad range of end users that includes 

scientists, park managers, park interpreters, and the general public. 

6.2 Laws and Policies 

Current laws and policies encourage federal programs to make use of existing spatial data 

before investing in the acquisition of new data sets. Specifically, Executive Order 12906, 

Section 3(d) states that each agency must adopt internal procedures to ensure the agency 

accesses the National Geospatial Data Clearinghouse before it expends federal funds to 

collect or produce new spatial data, to determine whether the information has already been 

collected by others, or whether cooperative efforts to obtain the data are possible. 

As part of any new project, the networks will use the National Geospatial Data 

Clearinghouse (geodata.gov) and NPS Data Store (science.nature.nps.gov/nrdata) for 

searching existing natural resources data set. The networks will also use other Internet 

resources, agency contacts, and other means to find data that may benefit its programs. 

6.3 General Standards and Guidelines 

General standards and guidelines for the acquisition and processing of programmatic and 

non-programmatic data (as defined in Chapter One) are provided below. Quality assurance 

and control procedures, which are essential for ensuring the production of superior data and 

information products, and which are components of all stages of the data life cycle, are 

discussed in greater detail in Chapter Seven. 

6.4 Programmatic Data 

Project leaders and data managers are responsible for ensuring data collection, data entry, 

verification, validation, storage, backup, and archiving are consistent with I&M network 

standards. In addition to general standard operating procedures that define network-wide 

requirements, protocol-specific SOPs may be developed that detail procedures or 
_________________________________________________________________________ 

50 

methodologies. Project leaders and cooperators on I&M projects should always receive a 

copy of their network’s relevant project specifications and protocols. 

6.4.1 Data Collection 

A wide range of tools is available for field data collection. All methods involve some tradeoffs in terms of expense, efficiency, and susceptibility to data entry/transcription errors. 

Project protocols should provide detailed specifications on how the following tools are used 

with individual projects. Justification for the choice of methods should also be provided. 

Field Forms are the most common method of recording field data. Field forms are 

inexpensive but require neat, legible handwriting. Manual field forms pose greater 

opportunities for error during the collection/data entry process compared with other methods: 

data noted on forms must be keyed later into project databases, sometimes by persons other 

than the original data recorders. This method tends to require more data entry time and more 

rigorous QA/QC. 

Field Computers increase data collection and data entry efficiency. Data can be directly 

downloaded to office desktops, eliminating the data entry step. QA/QC checks can be 

implemented in the database, further reducing data entry error and processing time. The 

drawback to field computers is usually greater expense, weight, battery life, complexity, and 

the risk of data loss if backups are not performed consistently. Two types of computers are 

frequently used in the field: 

Personal Data Assistants (PDAs): the small size and relative low cost of these devices make 

them attractive options for collecting field data. PDAs can be weatherized fairly easily and 

inexpensively. However, they have limited internal memory and data must be continually 

backed-up to larger storage devices. Most require additional processing/programming to 

transfer or create the structure of the master database in the field units. Working with 

relational database structures can be difficult to impossible if the database is complex, and 

uploading field data to a larger device requires specialized skills or software. 

Tablet PCs: these have the same properties as most laptops and provide the user with the 

convenience of a touch screen interface. They are bulkier, heavier, more expensive, and 

harder to weatherize than the PDAs, but more powerful as well. They are the best choice for 

field projects that are very data-intensive or rely on complex data structures. MS Access 

databases, as well as spatial data layers, can be directly transferred from the desktop to field 

units without additional programming. Data from the field units can in turn, be uploaded to 

the desktop with minimal effort. 

In some cases, the best choice is a combination of field forms and computers, for example, 

where large amounts of notes or comments need to be recorded in the field. 

Automated Data Loggers are mainly used to collect ambient information such as weather 

data or water quality information. These units must be properly calibrated and maintained, 

which requires proper training of field crews and SOPs that outline these procedures. Two 

types of automated data loggers are available: 
________________________________________________________________________ 

Chapter 6 - Data Acquisition, Processing, and Reporting 51

Permanently deployed devices provide continuous, real-time, or frequent data and are useful 

during conditions unsafe for field staff (e.g., severe storms, flood events). Data still must be 

retrieved; however, this can be accomplished remotely via satellite, landline, or cell phone. 

Providing sufficient and reliable power may be a challenge. Automated data-loggers require 

proximity to AC power, installation of solar power, or regular site visits to change batteries. 

Wilderness regulations may restrict the type of and location where a device is deployed. 

Portable hand-held devices are deployed for sampling only during site visits. 

GPS Units are generally used during field work to collect location (geographic coordinates, 

altitude) information. Two types of GPS units are most frequently used: 

Recreation Grade Units include both self-contained units (e.g., Garmin Map76CSx) and 

companion units for PDAs (e.g., Holux). These work well for collecting general position 

information but are not recommended for high-accuracy (sub-meter) location information. 

Survey Grade Units such as many Trimble GPS receivers are used for collecting accurate 

sub-meter location information. Increased accuracy comes at a greater cost.

Tape Recorders such as handheld micro-cassette tape recorders are useful for recording 

field data. Recorded observations are subsequently transcribed to paper or directly entered 

into computer files. As with other technological solutions there are drawbacks, including 

battery and tape maintenance, low environmental tolerance, and risk of failure. However, if a 

single data collector is in the field, tape recorders can provide an easily operated, high 

quality, efficient method of collecting data. 

All audio tapes used for recording field data should be labeled appropriately (e.g., date, site, 

project) and stored in the fire proof cabinet. Analog audio cassettes degrade over time and are 

a media that is quickly becoming outdated and obsolete. If this is a desired method for field 

data collection, efforts should be made to transfer the audio data to a more permanent audio 

format such as CDs or MP3 files. 

Photographs provide an excellent visual record of field visits and are useful for capturing 

point records of long-term study sites. They also serve well for automated data collection by 

remotely recording information using web cams or trip cameras. Slides and photographs 

should be stored and archived according to guidelines, and must have essential metadata 

associated with each image in order for the information to have long-term value. 

Remotely Sensed Data includes satellite imagery and aerial photography. Remote sensing 

can be a powerful tool for characterizing and analyzing landscape data, as well as readily 

capturing data within areas of low accessibility. Considerations for selecting remote sensing 

imagery include: 

 Accuracy and resolution needed 

 Frequency of measurement 

 Costs 

 Licensing for public use 

 Ortho-rectification standards 
_________________________________________________________________________ 

52 

Each remote sensing product is unique. It is imperative that users fully understand the 

product being used and that products be accompanied by well-documented metadata. Any 

projects involving remote sensing should include consultation with a professional remotesensing specialist. Project managers should consider the trade-offs between accuracy and cost 

among different imagery sources. 

A network’s GIS library can include satellite imagery coverage for most of the parks, along 

with base cartographic layers, digital orthophoto quadrangles, and natural resource theme 

layers. 

Any additional remote sensing data acquired will likely require some spatial or spectral 

processing depending on how they are received. All such data sets should be received in a 

geo-referenced format although some may need to be transformed to the network standard 

(UTM zone, NAD 83, meters). The extent of any additional processing will depend on how 

the data are to be used and what type of information is to be extracted from them. Specific 

requirements and procedures should be outlined in project protocols or SOPs. 

6.4.2 Data Processing 

Ideally, each project will have a database developed prior to the collection of any data in the 

field. I&M network databases are developed in conjunction with project protocols and are 

generally based on the Natural Resources Database Template (Chapter Five). Built-in 

procedures for data validation and QA/QC should be part of the database development and 

user interface. Data processing should encompass the following steps, and should occur as 

soon as possible after data are collected: 

 Field crews enter all data into an approved project database, under the supervision of the 

project manager. 

 Field crews periodically forward project data files to the project leader and/or data 

manager (refer to individual protocols for specific requirements). 

 All data undergo QA/QC procedures (see Chapter Seven for more specifics on data 

verification and validation). 

 The data manager maintains the master copy of the database and updates it with certified 

data files received from the project leader. 

 National databases are updated as per the procedures outlined in Chapter Ten. 

Spatial Data 

See network-specific standard for data collection with GPS and spatial data standards for 

complete details on methods for data collection and processing of spatial data. 

Photographs 

Photos taken as part of a project’s data collection protocol constitute data and need to be 

organized, documented and preserved in conjunction with all other project data. The 

processing, documentation, and storage of photographs, including digital photos, are detailed 

in network-specific SOPs. In general, the level of processing required will depend on the 

purpose of the photograph. Photos are regularly used by many park programs such as 

resource management, maintenance, fire management, and research. 
________________________________________________________________________ 

Chapter 6 - Data Acquisition, Processing, and Reporting 53

Editing of digital photos may be done to improve orientation or correct for lighting 

conditions (e.g., rotation to best orientation and removal of 'red eye'), but should never 

include alterations that change the original content of the photo. Photos may be cropped to 

remove edge areas that grossly distract from the subject. Poor quality photos can be deleted 

or destroyed, except where the subject is unique. Photos of medium quality should be 

assessed against existing photos of the same subject; if they duplicate a subject with no 

enhancement of quality or perspective, they may be deleted or destroyed. Working photos 

should be stored either in a workspace within a specific project or within a user's photo 

library. Digital aerial photos and imagery should be geo-referenced. All digital data photos 

should have geographic coordinates associated with them. 

Remote Sensing Data 

The processing of remotely-sensed data is often project specific. Therefore, project plans, 

protocols, and SOPs should document these procedures. Some steps will be common to all 

data sets, including: 

 Images are geometrically registered using nearest-neighbor resampling methods and coregistered to UTM NAD83. Registration accuracy is assessed 

 Images are radiometrically corrected and converted to exo-atmospheric reflectance 

 Atmospheric corrections are made, if applicable 

 All iterations (raw, intermediate corrections, and final) are maintained until project 

completion when raw and final products are archived. 

Vouchers 

The acquisition and processing of biological specimen vouchers will be guided by the 

policies outlined in network-specific SOPs, and under the guidance of the museum manager, 

curator, or permits manager for the park in which the specimens are collected. 

Project leaders will provide parks with material and data, in a prescribed MS Excel format or 

comma-delimited ASCII files (.csv) for automated uploading into ANCS+ and input to 

NPSpecies. Data provided to non-NPS curators will be in MS Excel format as well. 

Specimens are owned by the parks in which they were collected and are curated by park staff 

unless agreements have been made with outside institutions. See Chapter Eleven for more 

details. 

6.5 Non-programmatic Data 

A large amount of the data used to manage the natural resources of I&M network parks is 

collected by entities outside of the network (e.g., universities and other parks, agencies, and 

NPS programs). Locating and cataloging these kinds of data is referred to as data mining. 

Data collected and products produced by such efforts provide a great deal of information 

about park natural resources and are therefore relevant to many of its programs. These data 

can be classified as follows: 

 Current or ongoing – These are data that are currently being acquired or were recently 

acquired, are recognized to be of value, and are targeted for incorporation into existing or 

planned network projects. Their acquisition and use should follow very specific 

guidelines established in project or network protocols. Sources can be internal to NPS or 
_________________________________________________________________________ 

54 

from external sources. These data might be used to complement program data collection, 

to fill in gaps of missing data, or as a basis for comparison. 

 Legacy - These data are found and compiled through the data mining process. They may 

include vertebrate and vascular plant species data, other important natural resource 

inventory data, specimen or voucher data, bibliographic data, and existing monitoring 

data sets. 

Non-programmatic data can be obtained from academia, private organizations and non-profit 

groups, as well as local, state, and federal government agencies. Within the NPS, park, 

regional and national programs are all potential sources of information. Examples include: 

 NPS natural resource inventory programs – National-level programs collect data, 

maintain databases, assure data quality, and perform the trend analyses relevant to a suite 

of 12 natural resource topics, including vegetation, geology, soils, and air quality. 

 EPMT - Exotic Plant Management Teams (EPMT) collect and maintain data regarding 

the presence of exotic species in many parks, and develop and document the methods 

used to treat these species. Data are stored in the Alien Plant Control and Monitoring 

Database (APCAM) and maintained by the EPMT data manager. 

 Fire Program – Data on fire occurrence within the networks are maintained both at 

individual park and regional levels. National databases such as Fire-Pro, SACS and Fire 

Program Analysis (FPA) have been, and will be, used to maintain information regarding 

fire incidence and the resources dedicated to fire management. 

 GIS – The networks are supported by regional GIS specialists to help ensure regional GIS 

data are available and accurate. Much of these data are also available through the NPS 

GIS Clearinghouse. 

 Biological Resource Management - The regional Threatened and Endangered (T&E) 

Species Specialist provides management support and coordinates reporting of T&E 

species populations. 

 Research Permit and Reporting System – search tools enable users to search and view 

summaries of park-based research. 

 ANCS+ - Documents, photographs, specimens, and other research products are frequently 

archived at the park or regional level. 

Information collected during the data mining process should be maintained either 

electronically or as hard copy format depending on its original form, and should be cataloged 

and documented as fully as possible (Chapter Eight). Data should be cataloged to the 

appropriate repository as summarized in Table 6.3 and discussed in Chapter Ten. 
________________________________________________________________________ 

Chapter 6 - Data Acquisition, Processing, and Reporting 55

Table 6-1. Summary of possible data sources for different types of information and 

repositories where they are maintained 

Type of Data Possible Source Repository 

Bibliographic / 

Literature 

 Online literature databases (e.g., First 

Search or Biosis) 

 Library catalogs (e.g., academic or 

research institutions) 

 Park or regional archives through 

ANCS+ 

 Network parks: resource libraries, 

offices, file cabinets 

 NatureBib 

 Reference cabinets for 

hard copy materials 

 Digital archive for 

electronic materials 

Geographic Data  Regional centralized GIS data 

 Federal and state geographic data 

clearinghouses 

 Local, state, and federal government 

offices 

 Regional and park GIS specialists 

 NPS Data Store 

 Digital archive 

Biologic / Natural 

Resource Data 

 Voucher collections (museums, parks, 

universities) 

 Network parks: local or network 

computers 

 NPSpecies 

 Dataset Catalog 

 Digital archive 

Data mining is an integral part of project development, but efforts should not be limited 

solely to project development needs. This should be an ongoing process requiring regular 

data searches and visits to network parks to ensure that parks maintain and catalog as much 

material relevant to managing their natural resources as possible. Encouraging data sharing 

among parks will assist in this process and may alleviate the need for regular searches of park 

records. 

6.5.1 Data Collection 

The collection of data from non-programmatic sources should follow program specifications 

as outlined by project protocols or SOPs. Procedures should be standardized as much as 

possible and include: 

 Contacting data stewards and informing them of program needs 

 Establishing Memoranda of Understanding (MOUs) if needed, to address data ownership, 

dissemination, sensitivity, citation, or other use issues 

 Developing a contingency plan in case the data source is no longer available 

 Determining whether data can be consistently exported/imported and establishing a 

schedule 

 Determining how the data will be stored and integrated into the program 

 Determining how errors will be addressed 

 Determining if documentation is adequate and if not, completing where necessary 
_________________________________________________________________________ 

56 

 Identifying any interest in the exchange of program data and information with the outside 

program. 

 

Agency or organizational stewards of these data often have the expertise to conduct proper 

quality assurance and the capability to function as a repository and clearinghouse for 

validated data. In some cases, portions of external databases may be incorporated into 

network databases and thereby made more accessible to staff. 

6.5.2 Data Processing 

Much of the data identified during the mining process is likely to be the legacy type. As time 

and resources permit, legacy data meeting quality and relevance standards should be 

converted to file formats compatible with current software standards. Hardcopy references 

and other materials containing legacy data can be scanned and saved as .pdf files, and 

uploaded to NatureBib or the NPS Data Store where they become available to many. All 

legacy data sets should be reviewed and cataloged as follows: 

 Enter species-related data into NPSpecies (this is especially important for park-based 

biological inventories). 

 Enter all natural resource reports and publications related to network parks into 

NatureBib. Hard copies should be stored in the appropriate park or network collections 

and electronic copies uploaded to NatureBib. 

 All GIS data should be stored in the proper projection (UTM NAD83) and accompanied 

by FGDC-compliant metadata. 

6.6 Data Analysis and Reporting 

Data summary and analysis is essential to providing relevant and useful information for 

natural resource managers and scientists. Data managers and stewards must provide valid 

data in formats that support scheduled and ad hoc display, query, analysis, summary, and 

reporting. Routine and scheduled data summary, analysis and reporting requirements and 

procedures should be identified in project protocols. 

The development of data products should be guided by project objectives, protocols and data 

management SOPs. Products defined in advance, such as routine summaries and output 

formats can be automated through the use of queries and reports stored in a project's 

database. Project leaders should work with data managers to create, and test these queries. 

Queries can be used to view raw or summarized data, or to output either type as customformatted reports or as files that can be imported by other analytical tools (e.g., statistics 

software). Other queries can be built to facilitate data exploration and unscheduled analysis. 

Specific needs should be determined by individual projects. 

Most likely, data will be exported from project databases for most statistical analyses beyond 

means, standard deviations, and other descriptive statistics. Networks will typically use thirdparty statistical software (e.g., R, SAS, SPSS) for generating frequency distribution plots, 

tests for normality analysis of variance, time series analysis, and others. 
________________________________________________________________________ 

Chapter 6 - Data Acquisition, Processing, and Reporting 57

6.7 Changes to Procedures 

Changes to established vital signs data collection or processing procedures are discouraged 

unless there are acceptable, valid reasons for altering the methodologies. Ideally, problems 

are identified during the design and testing stages of the project and changes implemented 

prior to the collection of any field data. Protocols should attempt to identify any foreseeable 

issues that might occur as well as contingencies to address them. Once procedures are in 

production, changes are usually costly both in terms of data management resources required 

and in terms of potential erosion of existing data quality. 

Inevitably, unforeseen problems may occur that require procedure or protocol revision after 

data collection has begun. Significant changes to protocols must be approved by the principal 

investigator, project leader and data manager. The key official should evaluate the proposed 

changes and determine if additional peer review is required before accepting them. All 

changes should be carefully documented within project SOPs and any associated databases or 

metadata files. 

Any changes that occur as a result of a change in a project's protocol should be documented 

in the formal documentation developed for the database (Chapter Five). 

6.8 References and Resources 

Executive Order 12906. 1993. Coordinating geographic data acquisition and access: the 

National Spatial Data Infrastructure. (http://www.archives.gov/federalregister/executive-orders/pdf/12906.pdf) Accessed 10 February 2008. 

Geodata.Gov. http://geodata.gov. [access to maps, data, search options, articles, and other 

tools]. Accessed 16 January 2008. 

National Park Service Data Store. Secure online version. 

(http://science.nature.nps.gov/nrdata/). Accessed 16 January 2008. 

6.9 Related Network-level SOPs 

 Data mining in park units 

 Digitizing documents 

 Requesting park research permits 

 Data collection with GPS and portable data recorders 

 Developing GPS basemaps for use in GPS units 

 Using GPS photolink to georeference photos 

 Specifications for geospatial data deliverables 

 NPSpecies data entry procedures 

 NatureBib data entry procedures 

 NPS Data Store data entry procedures 

 Image management 

 Management of audio or video data 

 Collection and processing of specimens 

 Use of automated data loggers (setup, calibration, maintenance, etc.) 
_________________________________________________________________________ 

58 
________________________________________________________________________ 

Chapter 7 - Quality Assurance and Quality Control 59

CHAPTER 7. Quality Assurance and Quality Control 

The success of the Inventory and Monitoring Program is dependent on the quality of the data 

it collects, manages, and disseminates. Analyses performed to detect ecological trends or 

patterns require data that are recorded properly and have acceptable precision, accuracy, and 

minimal bias. Poor-quality data can limit detection of subtle changes in ecosystem patterns 

and processes, can lead to incorrect interpretations and conclusions, and can greatly 

compromise the credibility of the program managing it. 

Quality assurance (QA) can be defined as an integrated system of management activities 

involving planning, implementation, documentation, assessment, reporting, and quality 

improvement to ensure that a process, item, or service is of the type and quality needed and 

expected by the consumer. Quality control (QC) is a system of technical activities that 

measure the attributes and performance of a process, item, or service relative to defined 

standards (Palmer 2003). While QA procedures maintain quality throughout all stages of data 

development, QC procedures monitor or evaluate the resulting data products. 

7.1 Objectives 

The objectives of I&M network quality assurance and quality control are: 

 Ensure that inventory and vital signs monitoring projects produce high-quality and 

credible data that can be confidently used by managers, researchers and the public 

 Design, document, and implement standard quality assurance and quality control 

procedures that minimize or eliminate errors at every project stage. 

7.2 Laws and Policies 

Director’s Order #11B, “Ensuring Quality of Information Disseminated by the National Park 

Service,” was issued in order to promote data quality (Appendix 7A). It defines ‘quality’ as 

incorporating three key components: objectivity, utility, and integrity. 

Objectivity consists of: 1) presentation: whether disseminated information is being 

presented in an accurate, clear, complete, and unbiased manner within a proper 

context; and 2) substance: ensuring accurate, usable, and reliable information. 

Utility refers to the usefulness of the information to its intended users. 

Integrity refers to the security of information; e.g., protection from unauthorized 

access or revision to ensure that information is not compromised through corruption 

or falsification. 

Director’s Order #11B also specifies that information must be based on reliable data sources 

that are accurate, timely, and representative of the most current information available. These 

standards apply not only to NPS-generated information, but also to information provided by 

other parties to the NPS if the NPS disseminates or relies upon this information. 
_________________________________________________________________________ 

60 

The I&M networks hold as policy that techniques and procedures chosen for a project will 

maximize data quality. 

7.3 General Standards and Guidelines 

To ensure that I&M networks produce and maintain data of the highest possible quality, 

procedures have been established to identify and minimize errors at each project stage 

associated with the data life cycle (Figure 7-1). QA/QC procedures specific to any project 

must be detailed in a project's protocols and SOPs; however, some general concepts apply to 

all network projects. 

Although a data set containing no errors would be ideal, the cost of attaining 95%-100% 

accuracy may outweigh the benefit. Therefore, at least two factors are considered when 

setting data quality expectations: 

 frequency of incorrect data fields or records, and 

 significance of error within a data field. 

Errors are more likely to be detected when data set expectations are clearly documented and 

what constitutes a ‘significant’ error is understood. The significance of an error can vary both 

among data sets and within a single data set. For example, a two-digit number with a 

misplaced decimal point (e.g., 99 vs. 9.9) may be a significant error while a six-digit number 

with an incorrect decimal value (e.g., 9999.99 vs. 9999.98), may not. However, one incorrect 

digit in a six-digit species Taxonomic Serial Number could indicate a totally different 

species. 

QA/QC mechanisms are designed to prevent data contamination, which occurs when a 

process or event introduces either of two fundamental types of errors into a data set: 

 Errors of commission include those caused by data entry or transcription, or by 

malfunctioning equipment. These are common, fairly easy to identify, and can be 

effectively reduced up front with appropriate QA mechanisms built into the data 

acquisition process, as well as QC procedures applied after the data have been acquired. 

 Errors of omission often include insufficient documentation of legitimate data values, 

which could affect the interpretation of those values. These errors may be harder to detect 

and correct, but many of these errors should be revealed by rigorous QC procedures. 

The types of QA/QC needed for a project will vary based on data handling procedures 

(Figure 7-2). 
________________________________________________________________________ 

Chapter 7 - Quality Assurance and Quality Control 61

Figure 7-1. General course of data and associated quality assurance/quality control 

procedures. 

Data Entry 

Data Acquisition 

Project planning 

Verification 

Validation 

Dissemination 

Documentation 

Archiving 

Analysis and 

Reporting 

Data Stages QA/QC Activities 

 Backup/archive raw data 

 Obtain data results fom lab or other 

processing 

 Log what was collected 

 Data entry/training 

 Adherence to data entry procedures 

 Check records to ensure that data 

are entered and match originals 

 Review by project manager 

 Check that data make sense 

 Check for misspellings, out of range 

values, incorrect codes, logic errors. 

business rule violations 

 Note any corrections on originals 

 Follow project close-out procedures 

 Maintain, store, and archive data 

 Disseminate data and metadata 

QA/QC Procedure 

review by: 

project manager 

data manager 

 Database design 

 Collection procedures 

 Equipment maintenance/calibration 

 Data collection training 

 Data entry method planning 

 Identification of business rules 

 Verification/validation method planning 

 Formal certification by project manager 

 Quality statement by project manager 

 Sensitivity statement for each project 
_________________________________________________________________________ 

62 

Figure 7-2. Some common information management elements influencing the amount of 

QA/QC needed. 

7.4 Project Planning and Data Design 

Quality assurance begins with choice of project methods and information to be gathered. 

Quality assurance is achieved by stipulating that: 

 Common lookup tables are created for values recorded by multiple projects (e.g., weather 

variables, standard equipment, field personnel, etc.) 

 Each vital sign protocol has SOPs that address core information management practices 

(e.g., field crew training, use of handheld computers, equipment maintenance, and data 

backup, entry, verification, and validation, etc.) 

 Each project uses handheld computers for data collection if possible. If not, at a 

minimum, standardized field sheets are used 

 Databases adhere to the standards outlined in this plan (Chapter Five) 

 Database data entry forms, if necessary, resemble the field sheets 

 Automated error checking features will be included in database applications 

 Database application design will maximize the use of auto-fill, auto-correct, range limits, 

pick lists, and other constraints specific to projects 

 Database applications will include a means to track the date a record is created or 

modified, the name of the person creating/modifying the record, and errors reported on 

the data after dissemination 

 Database maintenance logs will be maintained for each network’s database and housed in 

association with database files. 

7.5 Data Collection 

Chapter Six addressed general data acquisition and initial handling as well as changes to data 

collection protocols. Attention to detail during the data collection phase, however, is crucial 

to overall data quality. Unlike a typographical error that occurs during data entry, an 

incorrect observation in the field is not easily corrected. 

The I&M Program adopts the following guidelines regarding data collection that affect data 

quality: 

 Field crews will receive proper training 

 Complex data model 

 Multi-stage data acquisition 

 No use of field sheets and/or data 

ranges 

 Data entry long after collection 

 Data entry by someone not 

familiar with data collection 

 Simple data model 

 Direct from field to database (handhelds, 

data logger, etc.) 

 Immediate data entry after collection 

 Data entry by personnel familiar with 

collection methods 

 Database control (ranges, common 

lookup tables, etc.)

more planning/control needed less planning/control needed 
________________________________________________________________________ 

Chapter 7 - Quality Assurance and Quality Control 63

 Any project using field equipment will include a calibration and maintenance SOP that 

will also specify establishment of an equipment maintenance log 

 Wherever possible and appropriate, data loggers or field-based computers will be used to 

collect data. When this is not possible, data will be recorded on pre-formatted, projectspecific data sheets that reflect the overall design of the project and are designed to 

minimize the amount of writing necessary to effectively record observations 

 When field sheets are necessary, or more appropriate, the format will be reflected in the 

computer data entry interface to help ensure all relevant information is recorded and 

subsequent data entry errors are minimized 

 Completed field forms will be proofed for errors each day in the field. Edits will be made 

by drawing a single line through the information to be changed, adding any replacement 

information in clear writing next to the original entry, and initializing the changes 

 Separate SOPs will describe the use of data loggers or field-based computers and will 

include direction for daily review and back-up. 

7.6 Data Entry 

Data entry is the process whereby raw data are transferred from paper field forms into an 

electronic data format. When data are gathered or stored digitally in the field (e.g., on a data 

logger), data entry consists of the transfer of data (downloading) to a file on another 

computer where they can be further manipulated. The goal of data entry is to transcribe field 

observations into a computer database with 100% accuracy, although errors are unavoidable. 

Subsequent data verification is conducted to ensure that raw data matches entered data. 

Following verification, data validation may result in changes to the entered data. Data entry 

should be a separate operation from data validation and care must be taken to not impose 

validation (beyond that automatically imposed by programming rules in a database) during 

data entry. 

The I&M Program adopts the following guidelines regarding data entry: 

 To the extent possible, data entry will be automated. This may simply entail downloading 

data from field-based computers but may include the application of new technology to 

allow for machine-driven data entry (e.g., voice- or optical character-recognition 

software) 

 Data will be entered as soon as reasonably possible after collection 

 Data entry will be completed by someone familiar with data collection. The project leader 

(with assistance from the data manager if needed) must ensure that data entry staff is 

familiar with the database software, database structure, and any standard codes used by a 

network. At a minimum, data entry technicians should know how to open a data entry 

form, create a new record, edit an existing record, and exit the database properly. They 

must also learn how to correct mistakes made while typing 

 Possibly, data could be entered by two qualified persons; one person to read the 

observations and the other to enter the data 

 Data will be entered into pre-designed database forms that resemble field sheets and 

maximize error control. 
_________________________________________________________________________ 

64 

7.7 Data Verification and Validation 

Data quality is assessed by applying verification and validation procedures as part of the 

quality control process. Data verification checks that the digitized data match the source 

data, while data validation checks that the data make sense. Although data entry and 

verification can be handled by personnel who are less familiar with the data, validation 

requires in-depth knowledge about the data. 

7.7.1 Data Verification 

The I&M Program adopts the following guidelines regarding data verification: 

 Project leaders are responsible for specifying in the project protocol one or more of the 

data verification methods available and ensuring proper execution. At the discretion of 

the project leader, additional verification methods may be applied 

 Data verification is carried out by staff thoroughly familiar with data collection and entry 

 All records (100%) should be verified against original source data 

 A subset of randomly selected records (10%) should be reviewed after initial verification 

by the project leader. If errors are found, the entire data set should be verified again 

 A record of the verification process for each data set, including number of iterations and 

results, will be prepared by the project leader as part of formal metadata generation (see 

Chapter 8 for more details) 

 Spatial data collected as part of the project will be viewed in a GIS and visually inspected 

for accuracy (e.g., points located outside park boundaries, upland locations occurring in 

water). 

Methods for Data Verification 

Each of the following methods has a direct correlation between effectiveness and effort. The 

methods that eliminate the most errors can be very time consuming while the simplest and 

cheapest methods will not be as efficient at detecting errors. 

Visual review at data entry: The data entry technician verifies each record after input and 

immediately corrects any errors. This method is the least complicated since it requires no 

additional personnel or software. Its reliability depends entirely upon the person keying data 

and thus, is probably the least reliable data verification method. 

Visual review after data entry: Upon completion of data entry, all records are printed and 

compared with the original values from the hard copy. Errors are clearly marked and 

corrected in the database as soon after data entry as possible. Reliability increases if someone 

other than the person keying the data performs the review. Alternatively, two technicians 

(one reading from the original data and one checking the entered data) can perform this 

review. 

Duplicate data entry: The data entry person completes all data entry as normal. Random 

records are then selected (e.g., every nth record) and entered into an empty replica of the 

permanent database, preferably by someone other than the person initially keying the data. A 

database query is then used to automatically compare the duplicate records from the two data 

sets and report on any mismatches. Disparities are manually reviewed and corrected if 
________________________________________________________________________ 

Chapter 7 - Quality Assurance and Quality Control 65

necessary. This method adds the overhead of retyping the selected records, as well as the 

creation of a comparison query. However, it becomes increasingly successful as the value of 

n decreases. Professional data entry services frequently use this method. 

Data verification can be improved by calculating summary statistics and identifying duplicate 

or omitted records. For example, the number of known constant elements, such as the 

number of sampling sites, plots per site, or dates per sample can be evaluated. Databases can 

also be built with controls to prevent duplicate records, although tests must be performed to 

identify missing records. The more checks that are devised to test for completeness, the 

greater will be one's confidence in the quality of the data set. 

7.7.2 Data Validation 

Validation is the process of reviewing computerized data for range and logic errors and may 

accompany data verification only if the operator has sufficient knowledge of the data and 

subject. More often, validation is a separate operation carried out after verification by a 

project specialist who can identify generic and specific errors in particular data types. 

General step-by-step instructions are not possible for data validation because each data set 

has unique measurement ranges, sampling precision, and accuracy. Specific guidelines 

should be written into all project protocols and SOPS. Invalid data commonly consist of 

misspelled species names or site codes, wrong dates, or out-of-range errors in parameters 

with well defined limits (e.g., pH). More interesting and often puzzling errors are detected as 

unreasonable metrics (e.g., stream temperature of 70°C) or impossible associations (e.g., a 

tree 2 feet in diameter and 3 feet high). These types of erroneous data are called logic errors 

because they produce illogical (and incorrect) results. The discovery of logic errors has 

direct, positive consequences for data quality and provides important feedback to the 

methods and data forms used in the field. Histograms, line plots, and basic statistics can 

reveal possible logic and range errors. 

The I&M Program adopts the following guidelines regarding data validation: 

 Project protocols will address a process for data validation that includes at least one of 

the available methods 

 Corrections or deletions as a result of data validation require notations in the original 

paper field records about how and why the data were changed, with the editor’s initials 

 Modifications of the field data will be clear and concise while preserving the original data 

entries or notes (i.e., no erasing) 

 Validation efforts will also include a check for the completeness of a data set since field 

sheets or other sources of data could be overlooked or inadvertently omitted. 

 Use of automated routines and/or data summary and visualization (e.g., histograms, line 

plots, and basic statistics) will be maximized to identify possible logic and range errors 

 Use of database programming will be maximized to control data entry. This will be 

achieved via the use of lookup tables and/or field-type design in a database (e.g., yes/no 

field types, input masks), and constraints such as valid ranges, uniqueness, referential 

integrity, and nullity. 
_________________________________________________________________________ 

66 

Methods for Data Validation 

The following general methods can be used as guidelines: 

Data entry application programming: Certain components of data validation are built into 

data entry forms. This method is essentially part of the database design and is discussed 

earlier in this chapter. Not all fields, however, have appropriate ranges known in advance. 

Caution must be exercised when using lookup tables to constrain variable values. Values 

occurring outside the range set by a lookup table (established during database design) may 

not always be invalid. As part of data validation procedures, the project leader is responsible 

for correct use of lookup tables or other automated value range control. 

Outlier Detection: According to Edwards (2000), “the term outlier is not (and should not be) 

formally defined. An outlier is simply an unusually extreme value for a variable, given the 

statistical model in use.” Any data set will undoubtedly contain some extreme values, so the 

meaning of ‘unusually extreme’ is subjective. The challenge in detecting outliers is in 

deciding how unusual a value must be before it can, with confidence, be considered 

‘unusually’ extreme. 

Data quality assurance procedures should not try to eliminate outliers. Extreme values 

naturally occur in many ecological phenomena; eliminating these values simply because they 

are extreme is equivalent to pretending the phenomenon is ‘well-behaved’ when it is not. 

Eliminating data contamination is perhaps a better way to explain this quality assurance goal. 

When an outlier is detected (via GIS, database, graphic, and statistical tools for ad-hoc 

queries and displays), the possibility of contamination will be evaluated and noted. 

Other exploratory data analyses: Palmer and Landis (2002) suggest calculations for 

assessments of precision, bias, representativeness, completeness, and comparability may be 

applicable and, for certain types of measurements, evaluation of detection limits may also be 

warranted. Normal probability plots, Grubb’s test, and simple and multiple linear regression 

techniques may also be used (Edwards 2000). 

7.8 Review, Conformance, and Communication 

The National Park Service requires QA/QC review and approval prior to communicating or 

disseminating data and information. Documentation of the QA/QC standards used in 

producing the information and that substantiate the quality of the information must be 

distributed with the related data and information. Mechanisms must also be in place for 

receiving and addressing comments or complaints pertaining to data quality (see also Chapter 

Ten). 

As part of the close-out and evaluation stage of each network project, QA/QC procedures 

will be reviewed by the project leader and recommendations for change will be included in 

the annual report. Similarly, network data management staff will review and revise the 

QA/QC procedures included in this information management plan and/or SOPs as needed. 

To ensure the highest quality, data stewards should conduct periodic audits to ensure 

compliance with the information management plan and vital signs protocols. Such quality 

checks promote a cyclic process of continuous feedback and improvement of the both the 

data and quality planning process. Audits may include verification of the following: 
________________________________________________________________________ 

Chapter 7 - Quality Assurance and Quality Control 67

 Data collection and reporting requirements are being met 

 Data collection and reporting procedures are being followed 

 Verification and validation procedures are being followed 

 Data file structures and maintenance are clear, accurate and according to plan 

 Revision control of program documents and field sheets are adequate 

 Calibration and maintenance procedures are being followed 

 Seasonal and temporary staff have been trained in data management practice 

 Metadata collection and construction for the program proceeds in a timely manner 

 Data are being archived and catalogued appropriately for long term storage 

The final step in the QA/QC process is preparation of summary documentation that assesses 

overall data quality. The statement of data quality is composed by the project leader and 

incorporated into formal metadata for the data set. Metadata should also provide information 

on the specific QA/QC procedures applied and the results of review. Typically, data quality 

information will be conveyed as part of FGDC-compliant metadata and will be available via 

the NPS Data Store. 

7.9 Roles and Responsibilities 

Producing and maintaining high quality data is the responsibility of everyone involved with 

the handling of project data. It is essential that each member of the team have a stake in data 

quality, and is responsible for the quality of the results generated from his or her tasks. While 

Chapter Four discusses data management-related roles and responsibilities, selected QA/QC 

duties are emphasized below. 

Project leaders need to: 

 be aware of QA/QC procedures in protocols and convey their importance to technicians 

and field crews 

 ensure compliance with the protocols 

 plan for and ensure proper execution of data verification and validation 

 review all final reports and information products. 

Project technicians must: 

 follow established protocols for data collection, data entry, and verification 

 inform the project leader and data manager of quality-related problems or difficulties. 

The data manager is responsible for: 

 developing network-wide SOPs to ensure data quality 

 making project leaders, technicians, and others involved aware of the established 

procedures and enforcing adherence to them 

 evaluating the quality of all data and information against NPS standards before accepting 

project data for dissemination outside the network 

 performing periodic data audits and quality control checks to monitor and improve 

quality control operations. 
_________________________________________________________________________ 

68 

7.10 References and Resources 

Edwards, D. 2000. Data quality assurance. Pages 70-91 in Michener, W.K., and J. W. Brunt, 

editors, 2000, Ecological data: design, management, and processing, Methods n 

Ecology Series. Blackwell Science Ltd., Malden MA. 

National Park Service. 2002. Director’s Order #11B: Ensuring quality of information 

disseminated by the National Park Service. 

(http://www.nps.gov/policy/DOrders/11B-final.htm) 

Palmer, C. J. 2003. Approaches to quality assurance and informatin management for regional 

ecological monitoring programs. Pages 211-225 in Busch, D. E. and J. C. Trexler, 

editors. 2003, Monitoring Ecosystems: interdisciplinary approaches for evaluating 

ecoregional initiatives. Island Press, Washington, D.C. 

Palmer, C. J., and E. B. Landis. 2002. Draft. Lake Mead National Recreational Area 

Resource Management Division: Quality System Management Plan for 

Environmental Data Collection Projects. 

7.11 Related Network-level SOPs 

 QA/QC and field data collection standards 

 QA/QC procedures for network vital signs data
________________________________________________________________________ 

Chapter 8 - Data Documentation 69

CHAPTER 8. Data Documentation 

Data documentation is perhaps the single most important step toward ensuring that data sets 

are useable well into the future. Data longevity is roughly proportional to the 

comprehensiveness of their documentation (Michener 2000). 

The term metadata is defined as information about the content, context, quality, structure, 

accessibility, and other characteristics of data. In addition to ensuring data longevity, 

metadata increases the possibility of data sharing and reuse for multiple purposes. Creating 

and maintaining comprehensive metadata is neither a simple nor quick process: it requires an 

up-front time investment for planning and organization, and an ongoing investment to keep it 

current. 

8.1 Objectives 

The objectives of data documentation are: 

 Ensure the longevity of data and their re-use for multiple purposes 

 Ensure that data users understand the content, context, and limitations of data sets 

 Facilitate discovery of data sets 

 Facilitate interoperability of data sets and data exchange 

8.2 Laws and Policies 

Executive Order 12906 requires all federal agencies to fully document all spatial data 

collected or produced since 1995, either directly or indirectly, with metadata that meet 

specific standards developed by the Federal Geographic Data Committee (FGDC) as outlined 

by its Content Standard for Digital Geospatial Metadata (CSDGM) (Federal Geographic 

Data Committee 1994). Executive Order 12906 also directs agencies to plan for legacy data 

documentation and provide metadata and data to the public. 

The NPS GIS Committee requires all new spatial data sets be described according to FGDC 

standards and the NPS Metadata Profile. The NPS Metadata Profile

(http://science.nature.nps.gov/nrdata/docs/npsprofile.cfm) extends the original ten sections of 

the CSDGM to include the FGDC Biological Data Profile, ESRI Metadata Profile (ESRI 

2003), and the NPS Profile. Profiles are simply formatted sections of information that are 

included in a formal metadata document. The NPS Metadata Profile is used by the Natural 

Resource and NPS Data Store for managing GIS and other data for both internal use and 

publication to the NPS GIS Clearinghouse within the NPS Focus Digital Library and 

Research Station. 

The FGDC Biological Data Profile (FGDC Biological Data Working Group, and USGS 

Biological Resources Division 1999) contains elements (i.e., specific information sections) 

for describing biological data sets (both spatial and non-spatial). Metadata that contain these 

elements can be disseminated to the National Biological Information Infrastructure (NBII, 

http://metadata.nbii.gov/) Clearinghouse and the NPS Data Store. 
_________________________________________________________________________ 

70 

The ESRI Metadata Profile (ESRI 2003) contains elements to better document aspects of 

ESRI data formats, particularly objects stored in geodatabases, and allow ArcCatalog to 

maintain metadata automatically. 

The NPS Metadata Profile contained within the NPS Metadata Tools and Editor comprises 

information about the park units to which the data pertain. 

8.3 General Standards and Guidelines 

Documentation is essential if an organization is going to maintain the value of information it 

collects. As personnel change and time passes, information about data can be lost and, 

consequently, the data lose their significance. Complete metadata descriptions of the content 

and accuracy of a data set will help ensure the appropriate and long-term use of a data set. 

Such descriptions also may provide some protection for the producing organization if 

conflicts arise over the misuse of data. 

From project development through final delivery of information products, I&M network data 

managers and project leaders must place a high priority on documenting the aims, quality, 

and meaning of data, and allow for the time this will take when scheduling. Detailed 

protocols provide an important source of information about the data produced by a project 

and therefore project leaders must track and document protocol versions. Metadata will 

adhere to strict standards, and their development will be guided by the practices described 

below. Crews will be trained to record decisions made in the field that affect data quality or 

meaning. Project leaders will start developing metadata at the onset of the project and set the 

tone for record-keeping throughout the course of the project. 

8.3.1 Content Standards 

Network metadata content standards will adhere to those set by FGDC and NPS policy as 

described above. The CSDGM consists of seven sections (Sections 1-7), all of which contain 

elements required for spatial data. The NPS Metadata Profile adds another section (Section 

0). The Biological and ESRI Profiles are added as elements to Sections 1-7. A summary of 

the CSDGM and NPS Metadata Profile sections is provided below. 

Section 0, NPS Information: purpose of the metadata, relevant park unit(s), and data steward. 

Section 1, Identification Information: who produced the data set, when and why it was 

produced, and where it is from. Constraints on access (e.g., for sensitive data) and use are 

also recorded in this section. Also included are the geographic extent, bounding rectangles, 

taxonomy, and analytical tools used in processing (for biological data). 

Section 2, Data Quality: the accuracy of attributes and geographic positions and the 

procedures used to ascertain accuracy. This section also documents the completeness and 

lineage of the data set. Lineage includes source(s) of the data and processing steps, and 

methodologies used (for biological data). 

Section 3, Spatial Data Organization: methods of spatial reference. Mandatory for spatial 

data. 
________________________________________________________________________ 

Chapter 8 - Data Documentation 71

Section 4, Spatial Reference Information: coordinate system definitions. Mandatory for 

spatial data. 

Section 5, Entity and Attribute Information: attribute names, definitions, codes and their 

meanings and other information essential to a basic understanding of the data. 

Section 6, Distribution Information: methods and contacts used for obtaining data. Also 

documents information critical for using biological data formatted in ASCII. 

Section 7, Metadata Reference Information: includes who created the metadata, when it was 

created, the profile used, and the frequency of update. 

Sections 8, 9, 10: repeated sections used throughout the above-cited sections 1-7. 

Metadata that are fully compliant with FGDC and NPS standards have entries in Section 0 

and all element fields in Sections 1-7 where the Optionality field contains the term 

‘mandatory’ or ‘mandatory if applicable.’ A mandatory element must be populated for every 

data set. A mandatory if applicable element must be populated if the data set exhibits the 

characteristic being documented by the metadata element. For example, the element defining 

the vertical coordinate system is mandatory if a data set contains elevation data. 

Metadata that are minimally compliant with FGDC and NPS standards have entries in 

Section 0 and all ‘mandatory’ and ‘mandatory if applicable’ element fields in Sections 1, 6, 

and 7, and Section 2 for biological data. These include the fields used by the NPS Data Store. 

Data sets documented to this extent can be distributed via the Data Store's online upload 

utility. 

8.3.2 Metadata Requirements for Different Data Types 

Spatial Data will contain, at a minimum, all of Section 0 and the required elements of 

Sections 1-7. 

Non-Spatial Data will include, at a minimum, all elements of Section 0, the required 

elements of Sections 1, 6, and 7, and Section 2 for biological data. The minimum 

requirements for non-spatial data therefore meet the requirements for minimum compliance 

with the FGDC and NPS standards. The Dataset Catalog application is a desktop tool for 

documenting a variety of non-spatial data, and allows the formatting and export of records to 

the NPS Data Store. 

Relational Databases will be documented according to the standards outlined above. 

Complete documentation will also include entity relationship diagrams, business rules, and 

programming code. The NPS Metadata Profile currently does not support this type of 

documentation, so it should be stored separately from the formal metadata, in a folder with 

the database. Relational databases should also use internal documentation, including 

comprehensive table and field descriptions. The NRDT structure contains a field in which the 

name of a corresponding metadata document can be entered. NRPC has also developed a tool 

that extracts a data dictionary from MS Access databases, which is helpful in preparing or 

updating documentation. 
_________________________________________________________________________ 

72 

Legacy Data will be documented to the extent possible according to the standards outlined 

above. Metadata records that accompany legacy spatial and non-spatial data sets are suitable 

for upload to the NPS Data Store if they include entries sufficient for minimum compliance 

with FGDC and NPS standards. Priority for legacy data set documentation is: 

 Data sets needed for current project development 

 Data sets used frequently by park staff or cooperators 

 Historic data sets archived for possible future use 

Data from Outside the Network are data that are generated and/or managed outside of I&M 

programs but used in analysis with I&M data or distributed in any manner by the NPS. These 

data require the same level of documentation produced for I&M-generated data, including 

but not limited to, data produced under contract with the NPS. Metadata will be requested 

from the originating entity by the network data manager or project lead. 

Generally, external data will not be posted on an I&M network or park local or wide area 

networks (LAN/WAN) without accompanying metadata. This will include any metadata 

downloaded with the data, plus additional information regarding date of download and any 

alterations made to the data by NPS staff. Staff posting data will make a reasonable effort to 

make up for any deficiency in the original metadata, but should not create new metadata for 

data from well-known sources (e.g., USGS digital line graph). NPS staff will occasionally 

post ‘value added’ external data (e.g., a digital elevation model clipped to park boundaries 

and converted to the standard projection) to the NPS Data Store, and associated metadata will 

reflect the source data as well as processing prior to upload. 

Sensitive Data. Metadata documentation (Section 1, Constraints on Access) provides one 

means of labeling sensitive data in order to ensure their protection and integrity over time. 

Sensitive data therefore will be documented according to the standards outlined above, 

although these data sets will not be uploaded to the NPS Data Store. Instead, they will be 

archived in secure locations on park and/or I&M network servers. These procedures will 

change as the NPS Data Store develops the procedures and acquires the necessary hardware 

to securely manage sensitive data. 

Digital Photos. A national metadata standard for digital photos is currently under 

development by NPS. In the meantime, digital photo metatdata should include, at a 

minimum:

 Author – the name of the photographer, with agency affiliation 

 Title – who or what is in the image (suitable for a brief caption) 

 Location – description of where the image was taken 

 Date – when the image was taken 

 Park code corresponding to image location 

 Access constraints – who may view the image (e.g., public, NPS only) 

 Copyright information – restrictions on using the image 

 Contact information – who to contact for further information 
________________________________________________________________________ 

Chapter 8 - Data Documentation 73

Electronic Documents. Most software programs provide a means of storing metadata within 

individual electronic files. In the case of Microsoft Word documents this is via the document 

properties item accessible from the file menu. For JPEG and TIFF files, the Exchangeable 

Image File Format (EXIF) data are embedded within the image file itself. Portable Document 

Format (PDF) documents also use the EXIF schema for file documentation. Although EXIF 

and Microsoft document properties are based on the Dublin Core basic element set and do 

not include all the elements of the CSDGM, use of these internal file documentation 

capabilities is encouraged. 

8.4 Metadata Tools 

ArcCatalog (from ESRI) is a multifunction application for managing spatial data and for 

editing FGDC compliant metadata. ArcCatalog uses stylesheets to display XML metadata in 

a format for easy viewing and editing. Because ArcCatalog metadata are linked to the data 

sets they describe, certain inherent properties of data sets, such as bounds, coordinate system, 

feature count, and attribute names, can be automatically populated and maintained in the 

metadata. 

NPS Metadata Tools and Editor (http://science.nature.nps.gov/nrdata/tools/) is a custom 

software application for authoring and editing NPS metadata. It extends the basic 

functionality of ArcCatalog for managing spatial metadata and provides a stand-alone tool 

for creating and manipulating non-spatial metadata outside of ArcCatalog. The Metadata 

Editor formats metadata according to the NPS Metadata Profile. Like ArcCatalog, editing is 

done with stylesheets. A variety of stylesheets are offered, each tailored to a specific type of 

metadata and displaying only the elements or sections pertinent to that type. NPS-specific 

stylesheets are based on the NPS Metadata Profile extension and contain all elements in the 

FGDC, ESRI, and Biological metadata standards and profiles plus NPS-specific elements. 

Metadata can be parsed using the USGS MetaParser program, which comes bundled with the 

Metadata Tools. Output format is XML, suitable for upload to the NPS Data Store. Metadata 

Tools includes utilities for searching, cataloging, parsing, and spell-checking metadata 

records. 

NPS Database Metadata Extractor is an add-in for MS Access 2000-2003. The extractor 

automatically harvests entity (table) and attribute (field) metadata from MS Access 

databases, including domains. It further allows the user to edit and review the harvested 

metadata and make batch edits and to export metadata to a FGDC-compliant XML file. 

Exported XML can be used in the Metadata Tools & Editor either by opening it to start a new 

metadata record or by updating with template to fill section 5 of an existing record. This tool 

will eventually become part of the NPS Metadata Tools & Editor. 

Metadata Parser is a program developed by the USGS that comes bundled with both 

ArcCatalog and the NPS Metadata Tools and Editor. It is used to validate metadata records 

by checking the syntax against the CSDGM and to generate compliant output files for 

posting to clearinghouses. The parser generates a textual report indicating errors in the 

metadata, primarily in the structure, but also in the values of some of the scalar elements 

where values are restricted by the standard. 

The “Metadata in Plain Language” questionnaire (Schweitzer 2006) is a user-friendly 

MS-Word document that can be used to elicit metadata needed to complete all FGDC 
_________________________________________________________________________ 

74 

required elements for non-GIS data sets. It currently does not include questions specific to 

the Biological Data Profile nor the NPS Profile and therefore, does not alone, meet the 

content standards specified by the NPS Metadata Profile. Additional information must be 

obtained to comply with these specifications. 

8.5 Work Flow Process 

I&M networks should establish a standard operating procedure for metadata generation and 

maintenance. In general, metadata development begins with project design and planning 

(Chapter Three). As the project progresses, metadata documentation will be completed with 

information such as field season dates, protocol changes, and taxonomic information. 

Completion will occur after the data set is certified by the data manager or project leader, 

which is then followed by upload to the NPS Data Store. The relationship between local 

applications and tools, and national-level storage and delivery system is illustrated in Figure 

8-1. 

Figure 8-1. Local and national applications and tools for metadata 

Once metadata are complete, the I&M network data manager or project leader saves one 

copy with the primary data set at the local level, and uploads an XML-formatted copy to the 

NPS Data Store. 

Metadata can easily be searched with Metadata Catalog, one of the tools in the NPS Metadata 

Tools and Editor. Metadata Catalog creates a Microsoft Access database that stores the 

location, filename and other information about all metadata files in a selected directory. 

8.6 References and Resources 

Executive Order 12906: Coordinating Geographic Data Acquisition and Access, the National 

Spatial Data Infrastructure (http://www.archives.gov/federal-register/executiveorders/pdf/12906.pdf) 

Repository: 

GeoSpatial One-Stop 

Access: public 

Repository: 

NPS Data Store (Oracle 

database) 

Access: Public 

Tools: 

 Arc Catalog 

 Metadata Tools & 

Editor 

Purpose: Create/edit 

metadata 

Tool: 

 Metadata catalog 

(MS Access database) 

Purpose: Organizes 

metadata files 

Local 

Level 

National 

Level 

Fully compliant 

meta-data 

Automatic 

posting of 

non-sensitive 

spatial data 
________________________________________________________________________ 

Chapter 8 - Data Documentation 75

Federal Geographic Data Committee, 1994. Content standards for digital spatial metadata 

(June 8 draft). Federal Geographic Data Committee. Washington, D.C. 

FGDC Biological Data Working Group, and USGS Biological Resources Division, 1999. 

Content Standard for Digital Geospatial Metadata - Biological Data Profile, FGDCSTD-001.1-1999 Federal Geographic Data Committee. Washington, D.C. 

Michener, W. K. 2000. Medata. Pages 92-116 in Michener, W. K. and J. W. Brunt, editors, 

2000, Ecological data: design, management and processing. Blackwell Science Ltd. 

Methods in Ecology Series, Malden, MA. 

National Biological Information Infrastructure (NBII). NBII Metadata Activities. 

(http://metadata.nbii.gov/portal/server.pt). Accessed 16 January 2008. 

National Park Service. Natural Resource Program Center. NPS Metadata Tools and Editor: a 

comprehensive editing tool for National Park Service metadata. 

(http://science.nature.nps.gov/nrdata/tools). Accessed 16 January 2008. 

National Park Service. 2007. Digital photo metadata standard. 

(http://focus.inside.nps.gov/docs/DigitalPhotoMetadata/index.html). Accessed 16 

January 2008. 

National Park Service. NPS Metadata Profile. 

(http://science.nature.nps.gov/nrdata/docs/npsprofile.cfm). Accessed 16 January 

2008. 

Schweitzer, P. 2006. Metadata in plain language. U.S. Geological Survey, Reston, Virginia. 

(http://geology.usgs.gov/tools/metadata/tools/doc/ctc). Accessed 10 February 2008. 

8.7 Related Network-level SOPs 

 Metadata development guidelines 

 Metadata interview form 
_________________________________________________________________________ 

76 
________________________________________________________________________ 

Chapter 9 - Data Ownership and Sharing 77

CHAPTER 9. Data Ownership and Sharing 

For the purposes of releasing data, the term sharing means providing data to an individual or 

entity upon request or as part of an agreement to do work that benefits the parks. The term 

dissemination includes releases to the public via publications or other means of delivery such 

as the NPS Data Store. Chapter 10 provides detailed standards and guidelines for data 

dissemination. Guidelines for data sharing, including sensitive data procedures, are described 

in this chapter. 

9.1 Objectives 

The objectives of data ownership and sharing guidelines are: 

 To establish a clear understanding of the ownership of data and any associated 

responsibilities 

 To protect sensitive data from unauthorized access and inappropriate use 

9.2 Laws and Policies 

The National Park Service defines conditions for the ownership and sharing of data, natural 

resource collections, and results based on research funded by the United States government 

in two principal documents - the Freedom of Information Act, 5 U.S.C. § 552, referred to as 

FOIA (Appendix 9A), and Office of Management and Budget (OMB) Circular A-110 (Office 

of Management and the Budget, 1999). 

FOIA stipulates that the United States government, including the National Park Service, must 

provide access to data and information of interest to the public, regardless of whether or not 

they were created by the federal government. FOIA is intended to establish a right for any 

person to access federal agency records that are not protected from disclosure by exemption 

or exclusions. Under the terms of FOIA, agencies must make non-protected data and 

information products available for inspection and copying in public reading rooms or on the 

Internet. 

The NPS is directed to protect information about the nature and location of sensitive park 

resources under one Executive Order and four resource confidentiality laws: 

 Executive Order No. 13007: Indian Sacred Sites (http://frwebgate.access.gpo.gov/cgibin/getdoc.cgi?dbname=1996_register&docid=fr29my96-149.pdf) 

 National Parks Omnibus Management Act (16 U.S.C. 5937) 

(http://www4.law.cornell.edu/uscode/html/uscode16/usc_sup_01_16_10_79.html) 

 National Historic Preservation Act (16 U.S.C. 470w-3) 

(http://www4.law.cornell.edu/uscode/html/uscode16/usc_sup_01_16_10_1A_20_II.html) 

 Federal Cave Resources Protection Act (16 U.S.C. 4304) 

(http://www4.law.cornell.edu/uscode/html/uscode16/usc_sup_01_16_10_63.html) 

 Archaeological Resources Protection Act (16 U.S.C. 470hh) 

(http://www4.law.cornell.edu/uscode/html/uscode16/usc_sup_01_16_10_1B.html) 
_________________________________________________________________________ 

78 

The OMB ensures that grants and cooperative agreements are managed properly. Federal 

funding must be disbursed in accordance with applicable laws and regulations. OMB 

circulars establish some degree of standardization government-wide to achieve consistency 

and uniformity in the development and administration of grants and cooperative agreements. 

OMB Circular A-110 establishes property standards within cooperative agreements with 

higher institutions and non-profit organizations. Section 36, “Intangible Property,” describes 

the administrative requirements pertinent to data and ownership, stipulating that all data and 

materials collected or generated using National Park Service personnel or funds become the 

property of the park unit from which they were collected. 

For additional information, see: 

 The Freedom of Information Act 5 U.S.C. § 552, As Amended By Public Law No. 104-

231, 110 Stat. 3048 (Appendix 9A). (http://www4.law.cornell.edu/uscode/5/552.html) 

 A Synopsis of Laws and Policies Governing Public Dissemination of Natural Resources 

Data (Appendix 9C). Also contains the text to Section 36 of OMB Circular A-110. 

 U.S. Department of the Interior FOIA regulations, instructions, and general information 

at http://www.doi.gov/foia/. 

 Draft Director’s Order #66: Freedom of Information Act and the Protection of Exempted 

Information (National Park Service, 2004a). 

(http://www1.nrintra.nps.gov/DO66/DO_66_Final_ Draft.doc) 

 Reference Manual RM-66A: FOIA processing (National Park Service, 2004b). 

(http://www1. nrintra.nps.gov/DO66/RM-66A-Draft.doc) 

 Draft Reference Manual RM-66B: Handling protected information (National Park 

Service, 2004c). (http://www1.nrintra.nps.gov/DO66/RM-66B-Draft.doc) 

9.3 General Standards and Guidelines 

Data and information will be shared internally through I&M network channels, externally 

through online databases and repositories, and by special request as appropriate, but only 

after quality control procedures have been fully implemented and data sensitivity assessed. 

9.3.1 Collaborative Agreements 

To ensure that proper ownership, format, and development of I&M network products are 

maintained, all cooperative or interagency work must be conducted as part of a signed 

collaborative agreement. Every cooperative or interagency agreement or contract involving 

an I&M network must cite OMB Circular A-110 under the Reports and Deliverables Section. 

The following shows appropriate language to use when citing Circular A-110: 

As the performing organization of this agreement, [institution or 

organization name] shall follow the procedures and policies set forth in 

OMB Circular A-110. 

Every cooperative or interagency agreement or contract must include a list of deliverables 

and products clearly defined within each agreement or contract. Details on formatting and 

media types that will be required for final submission must be included. Agreements and 

contracts must list all products expected to result from the project. These include, but are not 
________________________________________________________________________ 

Chapter 9 - Data Ownership and Sharing 79

limited to, field notebooks, photographs (hard copy and digital), specimens, raw data, and 

reports. 

Project leaders should provide a schedule of deliverables that includes sufficient time for the 

NPS to review drafts before scheduled final submissions.

9.3.2 Due Notification 

Network staff will notify investigators prior to making data sets available to the public. This 

will allow each investigator the opportunity to make a request in writing to further restrict 

access to the data set by the public. Network staff will review the investigator’s request and 

determine whether the request will be granted and for how long the data set will remain 

restricted. Details on how data and information products will be made available to the public 

are provided in Chapter Ten.

9.3.3 Access Restrictions to Sensitive Data 

With regard to natural and cultural resources, sensitive data are those that could be used to 

harm, remove, or destroy sensitive resources protected by units of the National Park System. 

Network staff members are responsible for managing access to sensitive data handled by 

their programs. These responsibilities include: 

 Identify and classify all potentially sensitive park resources and information. 

 Provide to superintendents a complete list of potentially sensitive park resources for 

which data may be collected as part of any project. The superintendent then determines 

what information should be protected. 

 Ensure that all protected information, digital and hardcopy, is properly identified and 

marked. 

 Ensure that all references to protected information are removed or obscured in any 

reports, publications, maps, data, or other form made available to the public. 

 Inform investigators working on network projects that: 

o All data and associated information must be made available for review by 

network staff prior to release in any format. 

o Any information classified as protected should not be released in any format 

except as approved in advance by the National Park Service. 

The network coordinator, NPS project liaison, or network data manager will identify all 

potentially sensitive park resources to the principal investigator for each project. Conversely, 

the principal investigators for each project must identify any known references to potentially 

sensitive park resources. 

Agreements with partners will include a standard confidentiality agreement which states that, 

among other things, the researcher will not share protected data or information with any other 

public, private, or academic party without channeling requests through the NPS project lead. 

Researchers may fulfill such requests provided there is a confidentiality agreement 

established between NPS and the new holder of the data. 

When sharing data and information on sensitive resources with other federal agencies, the 

other agency will be told of the need to channel any requests for the data or information 
_________________________________________________________________________ 

80 

through the NPS, as per NPS Director’s Order #66 (National Park Service 2004a) and 

accompanying Reference Manuals 66A (National Park Service 2004b) and 66B (National 

Park Service 2004c). 

9.3.4 Answering Requests under the Freedom of Information Act 

Data stewards will forward records requested pursuant to the FOIA to the requester via the 

Park FOIA Officer in a timely manner. Data stewards will maintain records subject to the 

FOIA in a manner so as to make them rapidly available and to leave no doubt that the most 

recent version of accurate, non-sensitive information is provided to requesters. Data stewards 

are responsible for reading, understanding, and following applicable laws, policy, and 

procedural guides. 

If information requested under the FOIA has not already undergone sensitivity classification, 

it will be thoroughly but rapidly assessed for presence of sensitive information and, if such 

information is found, the data steward will work with the appropriate park and regional FOIA 

Officers to formulate a response to the requester, which may include complete denial, 

complete fulfillment, or partial fulfillment once sensitive information have been cleared from 

the requested records. 

9.4 References and Resources 

Archaeological Resources Protection Act (16 U.S.C. 470hh) 

(http://www4.law.cornell.edu/uscode/html/uscode16/usc_sup_01_16_10_1B.html). 

Accessed 23 January 2008. 

Executive Order 13007: Indian Sacred Sites (http://frwebgate.access.gpo.gov/cgibin/getdoc.cgi?dbname=1996_register&docid=fr29my96-149.pdf). Accessed 23 

January 2008. 

Federal Cave Resources Protection Act (16 U.S.C. 4304) 

(http://www4.law.cornell.edu/uscode/html/uscode16/usc_sup_01_16_10_63.html). 

Accessed on 23 January 2008. 

National Historic Preservation Act 16 U.S.C. 470w-3. 

(http://www4.law.cornell.edu/uscode/html/uscode16/usc_sup_01_16_10_1A_20_II.ht

ml). Accessed 23 January 2008. 

National Park Service, 2004a. Draft Director’s Order #66: Freedom of Information Act and 

the Protection of Exempted Information. 

(http://www1.nrintra.nps.gov/DO66/DO_66_Final_ Draft.doc). 

National Park Service, 2004b. Draft Reference Manual RM-66A: FOIA processing. 

(http://www1. nrintra.nps.gov/DO66/RM-66A-Draft.doc). 

National Park Service, 2004c. Draft Reference Manual RM-66B: Handling protected 

information. (http://www1.nrintra.nps.gov/DO66/RM-66B-Draft.doc). 
________________________________________________________________________ 

Chapter 9 - Data Ownership and Sharing 81

National Parks Omnibus Management Act 16 U.S.C. 5937. 

(http://www4.law.cornell.edu/uscode/html/uscode16/usc_sup_01_16_10_79.html). 

Accessed 23 January 2008. 

Office of Management and the Budget, 1999. Circular A-110. 

(http://www.whitehouse.gov/omb/ circulars/a110/a110.html#1) 

The Freedom of Information Act 5 U.S.C. § 552, As Amended By Public Law No. 104-231, 

110 Stat. 3048 (http://www4.law.cornell.edu/uscode/5/552.html). Accessed 23 

January 2008. 

U.S. Department of the Interior FOIA regulations, instructions, and general information. 

(http://www.doi.gov/foia/). Accessed 23 January 2008. 

9.5 Related Network-level SOPs 

 General guidance: project deliverables 

 Approving information for distribution 

 Data sharing agreement 
_________________________________________________________________________ 

82 
________________________________________________________________________ 

Chapter 10 - Data Dissemination 83

CHAPTER 10. Data Dissemination 

Providing well-documented data in a timely manner is a primary goal of the I&M Program, 

and is essential to program success. This chapter describes the methods by which quality 

natural resource data and information collected by an I&M network are made available to 

park managers, researchers, educators, and the general public. 

10.1 Objectives 

The objectives of data dissemination are: 

 Ensure non-sensitive data are easily discoverable and obtainable 

 Ensure data that have not yet been subjected to full quality control are not released to the 

public, unless necessary in response to a FOIA request 

 Distribute data with complete and accurate metadata that clearly identify who collected 

the data, what data were collected, and where, when and how the data were collected 

 Identify and protect sensitive data from unauthorized access 

10.2 Laws and Policies 

Three major pieces of legislation form the basis for information dissemination and protection 

by federal agencies. They are the Freedom of Information Act, 5 USC Section 552 (FOIA), 

the National Parks Omnibus Management Act of 1998, 16 USC Section 5937 (NPOMA), and 

OMB Circular A-110 (Office of Management and the Budget, 1999). Each provides for the 

wide and proactive sharing of information and each recognizes instances where such sharing 

may be harmful. 

The FOIA requires that federal agencies provide access to most data and information 

holdings, whether developed by employees or by cooperators. Agencies are directed to post 

commonly requested items in public reading rooms and/or on public web sites. Nine 

exemptions provide for withholding information, such as that relating to law enforcement 

actions and confidential personnel records that are protected. Of these, the third exemption 

allows withholding information that is protected under other statutes. These include: 

 The Archaeological Resources Protection Act, which requires information on the location 

and nature of archaeological resources to be protected. 

(http://www4.law.cornell.edu/uscode/html/uscode16/usc_sup_01_16_10_1B.html) 

 The National Historic Preservation Act, which directs that information regarding historic 

resources should be withheld if disclosure would cause significant invasion of privacy or 

risk harm to historic resources. 

(http://www4.law.cornell.edu/uscode/html/uscode16/usc_sup_01_16_10_1A_20_II.html) 

 The Federal Cave Resources Protection Act, which prohibits release of information 

regarding the nature and location of caves. 

(http://www4.law.cornell.edu/uscode/html/uscode16/usc_sup_01_16_10_63.html) 

 Executive Order 13007, Protection and Accommodation of Access to Indian Sacred Sites, 

which allows for maintaining the confidentiality of Indian Sacred Sites. 

(http://frwebgate.access.gpo.gov/cgibin/getdoc.cgi?dbname=1996_register&docid=fr29my96-149.pdf) 
_________________________________________________________________________ 

84 

 The National Parks Omnibus Management Act (NPOMA), which provides protection of 

sensitive natural and cultural resource information. 

(http://www4.law.cornell.edu/uscode/html/uscode16/usc_sup_01_16_10_79.html) 

The NPOMA, heralded as the NPS “research mandate” (Harmon 1999), established the 

Cooperative Ecosystem Studies Unit and I&M programs. While NPOMA clearly requires a 

higher level of information sharing with the research community and other interested parties 

as well as use in management decisions, the exemptions in Section 207 allow for protection 

of information about resources not previously specified in other legislation. 

Another key policy statement, OMB Circular A-110 establishes federal government rights to 

use and share information gathered with federal support. The Circular also specifies that such 

information is subject to the FOIA and its exemptions. See Chapter 9 for details. 

10.3 General Standards and Guidelines 

I&M networks employ a number of distribution methods that ensure information collected 

and developed as part of network programs are made widely available to park employees, 

cooperators, and the public. 

Data and information are disseminated to the public principally through the Internet and only 

after quality control procedures have been fully implemented, unless a request is made 

pursuant to the FOIA with consideration to sensitivity and ownership classification. Data that 

are draft, under review, or otherwise not finalized may be posted on I&M network intranet 

sites for access by park or other NPS staff. 

Network staff will notify investigators prior to making data sets available to the public. This 

will allow each investigator the opportunity to request in writing to further restrict access to 

the data set by the public. Network staff will review the investigator’s request and determine 

whether the request will be granted and for how long the data set will remain restricted.

10.4 Data Distribution Mechanisms 

According to FOIA (specifically the 1996 amendments), all information routinely requested 

must be made available to the public via reading rooms and/or the Internet. An I&M 

network’s principal means of distributing inventory and monitoring data will be the Internet 

(Table 10-1). A number of Internet-based databases and repositories have been developed as 

part of the NPS I&M Program to store and disseminate a variety of natural resource 

information. They include: 

 I&M public web sites 

 National applications, including NPSpecies and NatureBib (public release pending) 

 The NPS Data Store 
________________________________________________________________________ 

Chapter 10 - Data Dissemination 85

Table 10-1. Distribution mechanisms for I&M network-related data 

10.4.1 Network Web sites 

I&M networks will regularly provide updated information about inventories and monitoring 

projects, including annual reports and detailed project reports through their individual public 

web sites (science.nature.nps.gov/im/units/) and intranet sites (nrintra.nps.gov/im/units). 

Networks will follow established I&M design and content standards. 

10.4.2 National Data Distribution Tools 

NPSpecies will be updated with observations and vouchers collected during the course of 

network projects, if these data are deemed important to the further documentation of species 

already present on certified park species lists, or constitute additions to these lists. NatureBib 

will be updated as new documents are produced or obtained via data mining efforts. Records 

in these databases are not publicly available; however, as they are transitioned to Serviceoriented Architecture a public component will be developed. 

Water quality data collected by I&M networks will be uploaded to EPA’s STORET National 

Data Warehouse. The NPS Water Resources Division has developed NPSTORET, which is a 

desktop database application for I&M networks to manage data entry, documentation, and 

transfer of water quality data. Data from NPSTORET are transferred periodically to 

STORET (Figure 10-1). Individual networks are free to use NPSTORET for data entry and 

maintenance, or to develop a customized database compatible for data exchange and 

delivery. 

Item Repository 

Reports -digital NatureBib / NPS Data Store; Network web 

site 

Reports - hard copy Park libraries, park archives, network office 

Protocols NPS Protocol Database, NPS Data Store 

Digital data sets – draft Network server; network Intranet 

Digital data sets – final / certified Network Internet; NPS Data Store 

Digital data – water quality NPStoret 

Digital data sets – sensitive Network server 

Project products 

Specimen vouchers 

Photographic film 

Park museum or archive, or other academic 

or NPS museum facility 
_________________________________________________________________________ 

86 

Figure 10-1. Flow diagram for water quality data from I&M networks to the STORET 

National Data Warehouse. 

Data from short-term studies (such as biological inventories) should be posted to NatureBib 

or the NPS Data Store within two years after data collection was completed, or following 

publication of the investigator’s results (whichever comes first). 

Data from long-term air quality monitoring conducted by network parks or by cooperators 

working with the parks, including visibility, gaseous pollutants (mainly ozone), atmospheric 

deposition (wet and dry), and meteorology are available through the NPS Air Resources 

Division web site at: http://www2.nature.nps.gov/air/monitoring. 

Long-term monitoring data collected as part of the I&M Vital Signs Monitoring Program will 

be posted to the NPS Data Store at appropriate regular intervals, or when trends analyses 

have been completed and reported on by the network. Before data are posted, the investigator 

or project leader will be asked to verify the final data set and metadata, and to identify any 

sensitive data or information. Sensitivity will be documented in the metadata which will 

accompany all data sets. 

Most data products resulting from the Natural Resources Inventories conducted through the 

NRPC and the I&M Program can be accessed via the Inventories web site at 

http://science.nature.nps.gov/im/inventory/index.cfm. 

10.4.3 Sensitive Data 

Data released outside of the federal government without a confidentiality agreement is 

considered a release of information under the Freedom of Information Act and triggers the 

application of the “release to one, release to all” principle. There are many venues for release 

of sensitive data that constitute release to the public. Therefore, information should be 

reviewed for sensitivity by qualified NPS staff prior to inclusion in these media. They 

include: 

 Internet posting 

 Interpretive programs, media, and activities 

 News releases 

 Resource management storing and sharing activities 

NPSTORET 

(desktop version) 

or NPSEDD files 

Networks 

NPS STORET 

(Oracle) STORET National Data 

Warehouse 

EPA 

Washington, D. C. 

WRD 

Fort Collins 

Edits or changes post 

quality assurance 

Annu Monthly a
________________________________________________________________________ 

Chapter 10 - Data Dissemination 87

 NEPA compliance documents 

Inadvertent access may be deemed a release depending on the circumstances. Network staff 

will institute security measures to ensure that any person uploading records to public 

databases is familiar with the procedures for identifying and abridging protected sensitive 

information. 

10.4.4 Feedback Mechanisms 

I&M network web sites will provide an opportunity for NPS staff, cooperators and the public 

to provide feedback on data and information gathered as part of I&M programs. A 

“comments and questions” link will be provided on the main page of the site for general 

questions and comments. A more specific “data error feedback” link will direct comments to 

network staff pertaining to errors found in web site-accessible data. 

The following procedure describes a process for networks to receive, verify, and correct data 

errors identified by public users: 

 Users send a notification through the network web site. 

 An acknowledgment of receipt is sent to the user. 

 Information is input into an error log table incorporated either in the project database or a 

specific error tracking database developed for the network. 

 Network staff determine whether the data in question are correct or incorrect. If correct, 

the user is informed that no corrections are to be made and the information stands. If 

incorrect, network staff make the appropriate corrections and notify the user and original 

data collectors. 

 The network web site is refreshed with the corrected information. 

10.5 References and Resources 

Archaeological Resources Protection Act (16 U.S.C. 470hh) 

(http://www4.law.cornell.edu/uscode/html/uscode16/usc_sup_01_16_10_1B.html). 

Accessed 23 January 2008. 

Executive Order 13007: Indian Sacred Sites (http://frwebgate.access.gpo.gov/cgibin/getdoc.cgi?dbname=1996_register&docid=fr29my96-149.pdf). Accessed 23 

January 2008. 

Federal Cave Resources Protection Act (16 U.S.C. 4304) 

(http://www4.law.cornell.edu/uscode/html/uscode16/usc_sup_01_16_10_63.html). 

Accessed on 23 January 2008. 

Harmon, D. 1999. The new research mandate for America’s National Park System: Where it 

came from and what it could mean. George Wright Forum 16(1):8-23. 

National Historic Preservation Act 16 U.S.C. 470w-3. 

(http://www4.law.cornell.edu/uscode/html/uscode16/usc_sup_01_16_10_1A_20_II.ht

ml). Accessed 23 January 2008. 
_________________________________________________________________________ 

88 

National Park Service. Air Resources Division. 

(http://www2.nature.nps.gov/air/monitoring/). Accessed 16 January 2008. 

National Park Service. Natural Resources Inventory & Monitoring Program, inventories. 

(http://www1.nrintra.nps.gov/im/inventory/index.cfm). Accessed 16 January 2008. 

[Intranet) 

National Parks Omnibus Management Act 16 U.S.C. 5937. 

(http://www4.law.cornell.edu/uscode/html/uscode16/usc_sup_01_16_10_79.html). 

Accessed 23 January 2008. 

Office of Management and the Budget, 1999. Circular A-110. 

(http://www.whitehouse.gov/omb/circulars/a110/a110.html#1) 

10.6 Related Network-level SOPs 

 Approving information for distribution 

 Data sharing agreement 

 Procedures for developing, posting, and updating network web site content 

 Guidance document: project deliverables 

 Data summary and analysis 
________________________________________________________________________ 

Chapter 11 - Records Management, Digital Data Maintenance, and Archiving 89 

CHAPTER 11. Records Management, Data Maintenance, 

and Archiving 

I&M networks are responsible for managing the documents, specimens, photographs, digital 

files, and other products resulting from network projects, administration, and activities. Much 

of the information generated by I&M networks will only increase in value and applicability 

over time. The potential for loss of data, documents, or objects can come from a variety of 

sources, including catastrophic events (e.g., fire, flood, and earthquake), user error, hardware 

failure, software failure or data corruption, theft, and intentional acts of vandalism. A 

fundamental responsibility of network data management is to establish procedures that will 

guarantee that I&M information will be accessible and usable for future generations. 

11.1 Objective 

The objective of I&M network records management, data maintenance, and archiving 

procedures is: 

 To ensure that I&M network information can be easily found, obtained, shared, and 

properly interpreted by a broad range of users in perpetuity. 

11.2 Laws and Policies 

Records are all documentary materials, including books, electronic data, maps, moving 

images, papers, photographs and sound recordings, made or received by the National Park 

Service during the transaction of public business. Directions for managing these materials, as 

well as electronic files, are provided in NPS Director’s Order 19: Records Management, and 

its appendix, NPS Records Disposition Schedule. NPS-19 states that all records of natural 

and cultural resources and their management are considered mission-critical records; that is, 

they are necessary to fulfill the NPS mission. NPS-19 further states: 

Mission-critical records are permanent records that will eventually 

become archival records. They should receive the highest priority in 

records management activities and resources and should receive 

archival care as soon as practical in the life of the record. 

Section N of Appendix B, which provides guidelines on natural resource-related records 

(including, specifically, the products from Inventory and Monitoring Programs), indicates 

that all natural resource records are considered “permanent,” that is, are to be transferred to 

the National Archives when 30 years old. It also indicates that non-archival copies of natural 

resource-related materials are “...potentially important for the ongoing management of NPS 

resources: and should not, in any instance, be destroyed.” 

Direction for the curation of specimens or other objects related to I&M research, and the 

archiving of reports, publications, maps, or other documents, are contained with the National 

Park Service Museum Handbook, Part II, and individual park museum Scope of Collection 

documents. 
_________________________________________________________________________ 

90 

The NPS General Support System (GSS) Backup Activity Plan (NPS 2007) and the NPS 

GSS Standard Procedures for Backup, Storage, & Recovery (NPS 2007b) both cover 

information relevant to the implementation of a network backup of electronic files by 

providing a minimum set of standards. These documents are provided by the NPS Office of 

the CIO and apply to all “headquarters, regions, and parks.” 

11.3 General Standards and Guidelines 

NPS Director's Order 19, Appendix B – Records Disposition Schedule has 40 pages devoted 

to classifying and filing NPS federal records and disposition specifications for each NPS 

federal record category. Generally, permanent federal records should be transferred to the 

National Archives when they are 30 years old. To the extent possible, an I&M network 

should comply with the most current NPS disposition schedule. 

I&M network procedures should also be established and documented to meet the following 

standards: 

 Where practical, maintain mission critical and permanent paper records in both hardcopy 

and electronic file format, and protect and preserve them indefinitely 

 Maintain data sets in file formats no more than two versions behind current software 

versions, or store in American Standard Code for Information Interchange (ASCII) 

format, complete with data and file documentation 

 Ensure information can be easily obtained, shared, and properly interpreted by a broad 

range of users 

 Ensure backup, storage, and recovery practices for archived electronic files equal or 

exceed the minimum standards established by the NPS Office of Chief Information 

Officer 

 Store all electronic files on servers in a networked environment using approved filenaming standards and file directory structures 

 Maintain all data, programmatic, and administrative electronic files indefinitely or to 

comply with Director’s Order 19 Appendix B, Records Disposition Schedule 

 Ensure all short- and long-term projects are well-documented, organized, and protected 

according to local and national standards and guidelines 

 Ensure all collected natural history specimens and objects are well-documented and 

preserved in perpetuity. 

11.3.1 Digital Data Maintenance 

Digital data pose particular challenges to long-term maintenance and preservation. 

Technological obsolescence is a significant cause of information loss, and data can quickly 

become inaccessible to users if stored in out-of-date software formats or on outmoded media. 

Effective maintenance of digital files depends on proper management of a continuously 

changing infrastructure of hardware, software, file formats, and storage media. Major 

changes in hardware can be expected every 1-2 years, and in software every 1-5 years (VogtO’Connor 2000). As software and hardware evolve, data sets must be continuously migrated 

to new platforms, or they must be saved in formats that are independent of specific platforms 

or software (e.g., ASCII delimited files). 
________________________________________________________________________ 

Chapter 11 - Records Management, Digital Data Maintenance, and Archiving 91 

An essential part of any archival holding (digital or non-digital) is its accompanying 

explanatory materials (Olson and McCord 1998). Effective long-term maintenance of 

information products depends on thoughtful and appropriate data documentation. 

Directory Structures 

Electronic files on I&M network file servers should be managed within a hierarchical set of 

directory structures, including folders for administrative files, data, publications, and reports. 

The primary repository for all electronic files should also be identified and access provided to 

all program staff. Key aspects of the file management strategy include the following: 

 To the extent possible, all applications work (e.g., spreadsheets, GIS, documents, 

databases) should be conducted from a common server 

 The server-based copy of all electronic files will be the primary version. Local electronic 

file versions on personal computers are not authoritative 

 Generally, all electronic files should be maintained in a networked environment that 

enables immediate retrieval. Although there are some exceptions, off-line storage and 

retrieval of electronic files from external media will be discouraged (except for the off-site 

backup storage of data files for security) 

 Working files are kept separate from archived products 

 Finished products are read-only 

 Standards such as naming conventions and directory structures should be enforced within 

shared and archived sections (e.g., libraries, GIS, databases). Although less stringent in 

other sections, these conventions are encouraged as good practice 

 Version control is implemented in both active and archived directories.

File Naming 

All electronic files should be named according to a set of guidelines and standards that apply 

to all electronic files created or maintained by staff or cooperators. The following guidance 

for file naming standards should be considered: 

 File names should be as short as possible, but include all mandatory information 

 The electronic file name should be unique, such that the chances for another electronic file 

having the same name on a local area network are unlikely 

 A versioning system of numbers (e.g., version1, version2, final, or v1, v2, etc.) should be 

used on documents 

 Generally, use lower case characters. However, it is an acceptable practice to mix upper 

and lower case letters in a filename to separate a concatenation of words, such as words in 

a title 

 Do not use spaces in file names 

 Do not use any special characters other than the underscore 

 Use the underscore to separate categories in an electronic file name 

 Use generally recognizable abbreviations or spell out words 

 Avoid uncommon acronyms, abbreviations and codes. Generally, avoid codes that require 

users to refer to another source for the code description. Agency-wide recognized codes 

such as park or network codes are acceptable 

 Use leading zeroes for numbers 1 through 9 
_________________________________________________________________________ 

92 

 Use the default file extension recommended by the software application associated with 

the file (Examples: .doc, .xls, .mdb, .rtf). 

Version Control 

Version control allows I&M network staff to manage changes made to data sets or 

documents, and provides an auditable trail of individual versions. As a general rule, to 

safeguard against loss or damage to data, changes or edits should not begin without having in 

place the ability to reverse them. In its simplest form, version control is simply saving a copy 

of a file before beginning work on it, and using an established version naming convention. 

Embedding dates or sequential numbers into file names, or establishing specific file directory 

structures are all techniques that can be used for simple version control. Version control can 

also include the MS Word “track changes” feature, or the SharePoint versioning features. 

The I&M network data manager determines the version control method and conventions that 

will be used. Software tools that assist in file management can be helpful; for example, a 

database that tracks revision histories, or backup routines that allow for automatic file 

renaming and archiving. Commercially-developed or open-source version control software 

may be an option. A version control system should: 

 Preserve previous versions of documents for possible recovery 

 Track documents as they change during the course of the developmental and editorial 

phases of document/report creation 

 Prevent conflicts between multiple collaborators by prohibiting multiple edits to the same 

file at the same time 

 Audit the document creation process by tracking who changes a file, when they make the 

change, and what changes they make 

 Reduce storage requirements by eliminating multiple copies of complete documents 

Backup and Recovery 

The need for backup and restore capabilities is critical to ensure proper safeguarding of 

irreplaceable information. Data recovery can be required due to catastrophic events (e.g., 

flood, hurricane, fire), software or hardware failure, or malicious activities. Every I&M 

network must have formal backup procedures documented and in place for both system- and 

workstation-level information. Storage procedures for data backup must include media 

rotations to both onsite and offsite locations. In addition, an essential component of any 

backup system also includes the regular testing of restore capabilities. 

I&M networks should discourage electronic file storage on personal computers and, to the 

extent possible, essential electronic files should be managed on a network server. In 

situations where an employee works with a computer that is off-network, each employee will 

be responsible for archiving and storing electronic files, with scheduled transfers of files to a 

network server that is backed up. 

11.3.2 Digital Archives 

Both electronic and hardcopy files should be consolidated and packaged for archiving when a 

project is complete or when milestones are reached. Project leaders are responsible for 

packaging electronic files and data, and for preparing materials for the curator. Network data 
________________________________________________________________________ 

Chapter 11 - Records Management, Digital Data Maintenance, and Archiving 93 

managers can be of assistance and provide guidance and clarification concerning the process 

or workflow. Project protocols should designate who will be responsible for product 

archiving, integration, backup, and distribution. Figure 11-1 illustrates the recommended 

paths that product archiving and storage follow. Procedures for hard-copy archiving are 

described in section 11.3.3 (below). 

Electronic File Archiving 

Digital files destined for archiving should meet the following requirements: 

 Comply with the network’s electronic file naming standards and hierarchical directory 

structure 

 Comply with data documentation and metadata standards 

 Clearly distinguish between sensitive and non-sensitive information 

 Integrate all deliverables, such as final reports, into appropriate catalogs, electronic 

libraries and clearinghouses, as described in this plan or specific project protocols.

Figure 11-1. General workflow for storage and archiving of electronic (blue) and hard copy 

(green) scientific research products. 

Short-term Projects
_________________________________________________________________________ 

94 

Short-term are those projects that usually last from one to three years and include individual 

research projects, inventories, or pilot work done in preparation for long-term research or 

monitoring. 

Upon project finalization, it is highly recommended that a set of ASCII comma-delimited 

text files be created for each data table comprising the data set. These files will be 

accompanied by a readme.txt file that explains the contents of each file, file relationships, 

and field definitions. The ASCII files are in addition to the native version of the data set 

(typically in flat or relational database formats) and will help ensure the data are usable in a 

wide range of applications or platforms. A tool such as Access_to_ ASCII.mdb (available 

from http://www1.nrintra.nps.gov/im/datamgmt/dtbases/links_sources/index.cfm), which 

automates the creation of these ASCII files from MS Access databases, will help with file 

conversion. 

A second reviewer (preferably the project leader) will evaluate the ASCII files and 

documentation to verify that tables, fields, and relations are fully explained and presented in 

a way that is useful to secondary users. All finalized files will be stored in the archive section 

of the project directory folders. 

In addition to creating ASCII files, staff should regularly update completed and archived data 

sets in older versions of MS Access, with the goal of having no data set more than two 

versions behind the current version. Converted databases will require thorough quality 

control if they are actively being used for data entry or analysis and if no documentation of 

prior quality assurance/quality control measures is available. Forms, queries, reports, and 

data entry will be thoroughly tested and corrected where any problems occur. All previous 

versions of the data set will be saved. 

Long-term Projects

Long-term projects include vital signs monitoring and other multi-year research and 

monitoring projects performed by the parks, other agencies, or cooperators, for which data 

acquisition and entry will continue for a period of four years or longer. 

Long-term monitoring databases will require periodic conversion to current database formats. 

Converted databases will require careful QA/QC to correct problems caused by 

modifications in programming code or other software changes. All active or long-term 

databases will conform to the current NPS software version standards. 

Long-term projects also will have variable long-term data archiving requirements. Raw data 

should be stored in perpetuity. Processed data sets should be archived as a complete unit 

before any modifications are made to project protocols. Depending on the project, it might 

also be necessary to preserve interim data sets (data “milestones”) over the long-term. 

Archived data sets or subsets destined for long-term archival will be saved, whenever 

possible, in their native formats in addition to ASCII text files. Specific data archiving 

requirements for ongoing projects should be spelled out in the Standard Operating 

Procedures for each project. 
________________________________________________________________________ 

Chapter 11 - Records Management, Digital Data Maintenance, and Archiving 95 

Spatial Data 

Spatial data sets essential to I&M networks will be maintained in a format that remains fullyaccessible by the current ArcGIS version. ArcGIS has maintained compatibility with 

previous data formats and, while shapefiles have retained functionality in ArcGIS, coverages 

may require conversion if they are no longer supported. 

Both uncorrected and corrected GPS data (e.g., .ssf and .cor files) should be archived in their 

native format in addition to the corresponding GIS files that are created. 

11.3.3 Object Curation and Document Archiving (non-digital products) 

The NPS Museum Management Program is responsible for the curation of physical objects 

related to park units (e.g., specimens) and the archiving of documents, publications, and other 

printed materials. The Automated National Catalog System (ANCS) is the data system used 

by the Museum Management Program to manage this information; a stand-alone copy of the 

application is maintained at each park with museum facilities. NPS museum management 

staff are responsible for managing this application and museum holdings. 

Park museum curators are a source of expertise, advice, and guidance on archiving and 

curatorial issues and have a role in almost all projects undertaken by I&M networks. Project 

leaders will involve park curators when projects are in the planning stage, to ensure all 

aspects of specimen preservation or document archiving are considered and any associated 

expenses are included in project budgets. Section 4.3.16 of Director's Order 24 requires 

"...project budgets to include funding for the basic management of collections that are 

project-generated." The costs for curation include cataloging, labeling, specimen preparation, 

initial storage of objects and specimens, and the organization and storage of project 

documentation. 

The overarching technical guidance for archival procedures is found in the NPS Museum 

Handbook. In particular, Part II, Appendix A – Mandates and Standards for NPS Museum 

Collections lists the cultural and natural history laws, regulations and conventions for NPS 

museum collections and should be reviewed prior to object collections. 

The long term management of physical objects and records will require the close cooperation 

of the individual collectors (whether NPS personnel, contractors, or permitted researchers) 

and local park museum personnel. Much of the responsibility will rest with the collector who 

remains the sole source for all curated documentation and the principal authority for essential 

collection information. 

Successful collaboration with NPS museum staff includes adequately preparing materials for 

accession. The types of information neeed by curators include: 

 A project summary sheet listing project name, research permit, abstract and purpose, 

contact information, sensitivity, use of materials, and all materials included in the archive 

submission 

 Clearly labeled materials with appropriate administrative boundary name (e.g., park, 

network), date(s), accession number, catalog number (if assigned), and project number. 

 Compliance with archival paper and folder type requirements 

 Printed and labeled photos 
_________________________________________________________________________ 

96 

 Voucher specimens labeled according to the NPS Museum Handbook and any loan 

paperwork if specimens will reside outside an NPS facility 

 A .csv file containing voucher attribute information formatted for automated data transfer 

to the ANCS data system 

 A CD or DVD of all related, electronic materials and labeled with appropriate 

administrative boundary name, date created, date(s) of information, accession number, 

project number, list of contents. 

Natural History Specimens 

Natural history specimens collected under the auspices of an I&M network, along with 

associated field notes, should be transferred to the park in which they were collected for 

either inclusion in the parks’ museum collections or for transfer to a repository approved by 

the park. In this latter case, the park will enter into a formal, documented relationship with 

the repository and the specimens will be considered to be “on loan” with clearly stated terms 

and responsibilities. All loans are subject to the approval of the park superintendent. 

Park curators should be involved at an early stage in the permitting or agreements process; 

early cooperation between curators and collectors will facilitate compliance with the current 

NPS Management Policies. Park curators can provide the collector or network with a preformatted MS Access database template, the use of which will greatly simplify eventual 

importation of catalog data into the ANCS. At a minimum, parks will need such data in 

comma-delimited format (.cvs) for automated uploading. 

Photographs 

Archivists have been reluctant to fully embrace digital photography because of a concern 

that, with the accelerating rate of technological change, documentary heritage is in danger of 

being lost in the information age (Cox 2000). While a network maybe prepared to accept 

both digital and analog photographs, the particular photographic methods to be used by any 

given project should be developed jointly by the project leader and network staff or 

cooperators. Early involvement of curatorial staff will insure that the specific preservation 

considerations of particular photographic methods are understood and considered. 

For projects using analog photos, networks are strongly encouraged to use Kodachrome 

35mm slide film, which has the longest dark-storage dye stability of any color film (Wilhelm 

and Brower 1993), or other professional-grade slide film. Slides should be labeled using 

indelible pigment, pH-neutral ink (e.g., Pigma Micron), or using laser-printed archivalquality slide labels. Labels must include the following information: 

 Title – who or what is in the image 

 Location – where the image was taken 

 Date – when the image was taken 

 Park Code 

 Access Constraints – indication if the image should be restricted due to sensitivity 

Additional important information to associate with images includes copyright information 

(restrictions on using the image) and contact information (who to contact for further 

information); the geographic location with UTM NAD83 coordinates (based upon a 
________________________________________________________________________ 

Chapter 11 - Records Management, Digital Data Maintenance, and Archiving 97 

network’s mapping standard) and datum. All slides should be placed in archival 

polypropylene slide-sleeves and stored away from direct light, in climate-controlled 

conditions, and preferably in an archival box. 

Additionally, slides may be scanned and saved digitally in Tagged Image File Format (TIFF). 

If scans are used as the primary means of distributing or reproducing the images, the physical 

life of the original slides will be greatly extended. 

If photographic prints are desired, staff and cooperators are strongly encouraged to use true 

black-and-white films (e.g., Ilford Delta, Kodak T-Max or Tri-X). Prints and negatives will 

be stored in individual polypropylene sleeves and within archival boxes. Each print will be 

labeled on the back, using archival-quality labels that are either laser-printed or hand-labeled 

with the same information elements required for slides. If a contractor is submitting 

photographs, corresponding TIFF files may also be submitted. 

Every image, regardless of format, should be entered into a network photo management 

database, where attributes such as electronic file name, keywords, project, photo description, 

photographer, date, and location are cataloged. The National Park Service has developed and 

adopted a set of suggested metadata attributes 

(http://focus.inside.nps.gov/docs/DigitalPhotoMetadata/index.html). All photo files and the 

associated photo database should be housed on the archive portion of the network server. 

11.4 References and Resources 

36 CFR 2.5: Research Specimens (Code of Federal Regulations, 2001). Provides direction 

for managing natural history collections 

Cox, R. J. 2000. Searching for authority: archivists and electronic records in the New World 

at the fin-de-siècle. First Monday 5:1. 

(http://firstmonday.org/issues/issue5_1/cox/index.html). 

National Park Service, 2001b. Director's Order 19, Appendix B: Records Disposition 

Schedule. Revised May, 2003. U.S. Department of the Interior, National Park 

Service, Washington, D.C. 

National Park Service. Natural Resources Inventory & Monitoring Program, I&M network 

data management: code and tools. 

(http://www1.nrintra.nps.gov/im/datamgmt/dtbases/links_sources/index.cfm). 

Accessed 16 January 2008. [Intranet site] 

National Park Service. NPS Digital Photo Metadata Standard. 

(http://focus.inside.nps.gov/docs/DigitalPhotoMetadata/index.html). Accessed 16 

January 2008. [Intranet site] 

National Park Service, 2007. NPS General Support System, Backup Activity Plan. U.S. 

Department of Interior, National Park Service, Washington, D.C. 
_________________________________________________________________________ 

98 

National Park Service, 2007b. NPS GSS Standard Procedures for Backup, Storage, & 

Recovery. U.S. Department of Interior, National Park Service, Washington, D.C. 

National Park Service. 2000. NPS Director’s Order 24: Museum Collections Management. 

Olson, R. J. and R. A. McCord, 1998. Data Archival. Pages 53-57 in Michener, W. K., 

Porter, J. H., and S. G. Stafford. Data and information management in the ecological 

sciences: a resource guide. 

Vogt-O’Connor, D., 2000. Planning digital projects for preservation and access. National 

Park Service Conserve O Gram 14:4. NPS Museum Management Program, 

Washington, DC. (http://www.cr.nps.gov/museum/publications/conserveogram/19-

21.pdf) 

Wilhelm, H. and C. Brower, 1993. The permanence and care of color photographs: 

traditional and digital color prints, color negatives, slides and motion pictures. 

Preservation Publishing Company, Grinnel, Iowa. 

11.5 Related Network-level SOPs 

 Network I&M Program Checklist of Project Specifications 

 Digital Photo Management Strategy 

 Electronic File Naming Guidelines and Standards 

 Program Guidance and Rules for File Directory Structure 

 Network Project Template Directory Structure 

 Standards and Guidelines for Backup, Storage, and Recovery 

 Network Archive and Storage Locations 
________________________________________________________________________ 

Chapter 12 - Project Tracking and Documentation 99

CHAPTER 12. Project Tracking and Documentation 

I&M networks face the challenge of managing multiple projects, contracts, and agreements; 

budgets; timelines and deliverables; and permanent, term and temporary staff. As networks 

develop and become fully staffed, many have found that a project tracking and 

documentation system is necessary to function effectively. 

12.1 Objectives 

The objective of project tracking and documentation procedures are: 

 Efficiently manage and coordinate contracts, permits, agreements, and associated 

timelines, schedules, and budgets 

 Ensure project products are delivered on time and per specifications 

 Manage information needed for annual reporting and accountability 

 Improve accountability for I&M network natural resource inventory and monitoring 

efforts and provide a means of tracking accomplishments 

12.2 Laws and Policies 

There are no overarching NPS or DOI policies related to specific project tracking methods or 

requirements. Individual agreements established by I&M networks contain specific 

requirements, timelines and deliverables that must be attained. 

The NPS Associate Director of Stewardship and Science established in 2001 the requirement 

that each I&M network submit an Annual Administrative Report and Workplan at the end of 

each fiscal year. 

12.3 General Standards and Guidelines 

12.3.1 Project Organization 

All project electronic files should be stored in an intuitive project directory structure that is 

clearly understood by all network staff. Network digital directory structures should be 

organized at the project level, such that most or all digital files associated with a project are 

filed under a common root directory. Project file names will adhere to the naming 

conventions established by the network. Physical objects acquired as part of a project will be 

stored according to the network’s specification for records management and object curation. 

12.3.2 Project Tracking 

Networks are encouraged to implement a project tracking system or database that will serve 

as the primary organizational tool for cataloging and searching information on I&M projects. 

This system should, at a minimum: 

Maintain a master list of projects: project leaders and other users will be able to locate 

rapidly information related to completed, current, or upcoming projects (e.g., objectives, 

contact information, status, funding sources, project codes from various NPS systems) 
_________________________________________________________________________ 

100 

Track product deliverables: a list of project deliverables will allow oversight of permitting 

contracting, content and formatting specifications, delivery schedules, and disposition 

schedules. 

 

A project tracking database should be hosted on a network file server and be accessible by all 

appropriate staff. Custom queries or reports will help administrators manage projects and 

facilitate reporting on project status, accomplishments and delivered products. 

12.3.3 Additional Project Metadata 

Long-term monitoring projects may require documentation beyond the scope of established 

FGDC standards. Documentation should be provided for algorithms, output files, and 

analytical products which may reside in different systems and formats, and could potentially 

be overlooked when distributing or applying project data. Data use and data request histories, 

and information on secondary research or publications resulting from long-term monitoring 

projects, should also be maintained. The network’s project tracking database potentially 

could be used to organize this information. Specific methods for documenting this 

information will be tested for ease of use and are likely to evolve over time as needs become 

apparent and new solutions are developed. 

12.4 References and Resources 

12.5 Related Network-level SOPs 

 Checklist for initiating a new project 

 Project specifications and deliverables 

 Project management database application 

 Project data life cycle guidance 
________________________________________________________________________________

Chapter 13 - Implementation 101 

CHAPTER 13. Implementation 

The Inventory and Monitoring Program data management plans contain practices that may be 

new to many NPS staff and cooperators. While this document and the accompanying 

network-level data management plan and SOPs offer practical guidelines and solutions, 

successful implementation will require continuous formal and informal education of staff and 

cooperators, and a long-term and disciplined commitment on the part of data managers and 

network staff to make it all work. 

13.1 Objectives 

The objectives for a plan to implement I&M network data management practices and 

procedures are: 

 Ensure that the procedures outlined in this plan and related SOPs are put into practice 

 Provide a framework to realistically assess related network procedures and adjust them as 

needed 

 Establish benchmarks so that implementation progress is measured and evaluated 

13.2 Laws and Policies 

Implementation of an I&M network data management plan follows requirements stemming 

from federal law, Executive Orders, Director’s Orders, or national Inventory and Monitoring 

Program guidance. The Inventory and Monitoring data management plan is a component of a 

broader decision support system (NPS-75) required for evaluating the state of national 

parkland resources. The network level data management plan puts these requirements into 

context, and provides operational guidance for implementing them. 

13.3 General Standards and Guidelines 

Implementing a data management plan requires that many related components come together 

efficiently. Each network data management plan should ensure or accomplish all of the 

following: 

 Data management objectives are clear, quantifiable, achievable, and supportive of the 

I&M network goals 

 Protocols and standard operating procedures are followed so that data are consistent, 

comparable, secure, and of highest quality 

 Data management standard operating procedures illustrate tasks, roles, and 

responsibilities; are reasonable and achievable, and minimize duplication of effort 

 I&M network data management programs provide superior infrastructure and support to 

I&M network and park staff 

 Milestones are set periodically to allow for regular, critical evaluation of objectives and 

time for planning alternative solutions 

 Maintain data management staff expertise in current technology, and provide 

opportunities for training in new technologies. 
_________________________________________________________________________ 

102 

13.4 Education and Training 

Training and education of both data management staff and network staff will be critical in 

consistently obtaining high quality data. Data management staff will require solid working 

knowledge of software, hardware and business processes. Park staff and cooperators must be 

familiar with the tools, procedures, and guidelines outlined in SOPs, which can be 

accomplished through formal training sessions and more informal one-on-one assistance. 

13.5 Milestones 

I&M network data management planning documents and SOPs should be dynamic, with 

accommodation made for periodic review of progress. The following milestones are 

suggested for implementing each plan. 

13.5.1 Years One through Five: 

The following outcomes should be achieved within the first five years of implementing a 

network data management plan: 

 All network staff understand the fundamentals of data management, which include: 

o File and folder management 

o Network shared drive organization 

o Documentation (e.g., metadata formats and process) 

o Quality assurance and quality control 

o Storage, backup, and archiving 

 Data management practices are improved by implementing: 

o Conceptual Data Models for Vital Signs monitoring protocols 

o Testing of data entry prior to field work. 

 Common standard operating procedures are used for multiple protocols where possible 

 Data management staff are directly engaged, in the earliest possible stages, in all aspects 

of vital signs monitoring protocols 

13.5.2 Five Years and Beyond 

After five years, the network data management plan and associated SOPs will be fully 

reviewed and revised, and will incorporate the lessons and practices learned over the first 

five years. Emphasis will likely increase in the following areas: 

 Data reporting, synthesis, and analysis 

 Integration of data with other offices, agencies, or programs 

 Direct access to data via web services or service-oriented architecture frameworks 

 Migration of data to new platforms and applications. 

13.6 References and Resources 

13.7 Related Network-level SOPs 

 File and folder naming conventions 

 Documentation 

 Quality Assurance/Quality Control
Appendix A A-1 

Appendix A. Glossary of Terms 

ArcIMS, ArcSDE (Arc Internet Map Server and Arc Spatial Database Engine) Geographic 

information system (GIS) software applications developed by the Environmental Systems 

Research Institute (ESRI). These applications provide tools for managing large, complex 

spatial data sets within a relational database management system (ArcSDE), and serving the 

data over the Internet (ArcIMS). 

Best practice A technique, methodology, or standard operating procedure that, through 

experience and research, reliably leads to a desired result. 

Certified data and metadata Completed data and documentation for short-term projects, or 

one season of completed data for long-term monitoring projects. Certification is a 

confirmation by the project leader that data have passed all quality assurance requirements 

and are complete and ready for distribution. Metadata records include the detailed 

information about project data needed for proper use and interpretation. 

Conceptual data model A detailed model that shows the overall structure of organizational 

data, independent of any particular database management system or other implementation 

considerations. Conceptual data models are typically produced as the first step in system 

design, often presented as entity relationship diagrams, and frequently a precursor to the 

logical data model. 

Data Distinct measurements or observations of a variable, usually formatted in a special 

way. They include symbols or representations of facts or ideas that can be communicated, 

interpreted, or processes by manual or automated means. 

Tabular data are usually organized into logical tables of records and fields, arranged in a 

matrix of rows and columns. Tabular data can be displayed, manipulated, and stored as 

simple text files or in applications software (e.g., spreadsheets, relational databases). 

Spatial data are any data that reference geographic coordinates. GIS data always contain 

these references; tabular data that contain spatial references are also considered spatial. The 

terms GIS data and spatial data are often used interchangeably. 

Raw data are data in their original form, i.e., data that have not been altered, summarized, or 

grouped into broader categories. Raw data can exist in many forms: as hand-written 

information on field data forms and in notebooks; as unaltered photographs; sound and video 

recordings; remote sensing imagery; or Global Positioning System (GPS) files. 

Derived data are raw data that have been processed, or converted to another form using some 

automated or manual process. Raw natural resources data are often processed and packaged 

for summation, statistical analysis, and graphical display, or the production of maps and other 

information products. 

GIS (geographic information system) data contain information about the location and shape 

of, and relationships among, features on the surface of the earth and are usually stored as 
Appendix A A-2 

geographic coordinates and topology. Topology is used to compare the geographic locations 

of features relative to one another (e.g., roads connected to a highway, two vegetation 

polygons adjacent to one another). 

Legacy data are data that are at risk of becoming lost, unusable, or obsolete due to software 

or metadata limitations. 

Programmatic data are data developed specifically by or for a program or project. 

Programmatic data are usually acquired based on well-defined objectives and specific 

requirements. 

Non-programmatic data are data obtained from an external source, but that are of value to a 

program or project (e.g., county land parcel information, weather data managed by the 

National Weather Service, or taxonomic information managed by the U.S. Department of 

Agriculture). 

Sensitive data are data that through loss, unauthorized access, or modification, could be used 

in such as way as to adversely affect valuable resources, the national interest, the conduct of 

federal programs, or individual privacy. Examples of sensitive natural resources data might 

include the locations of rare flora or fauna species, caves, or cultural sites. 

Data set A grouping of related data, such that the asemblage of the information will be 

meaningful to prospective users. 

Dataset Catalog A Microsoft Access database application developed by NPS to 

accommodate spatial and non-spatial metadata. The Dataset Catalog is not fully FCDCcompliant; therefore, has been used primarily for documenting non-spatial data sets. Ongoing 

development was stopped in 2007 and the database will be replaced as WASO completes the 

transition of its systems to a service-oriented architecture framework. 

Edit log A means of tracking changes to certified data. 

Document Recorded information regardless of physical form or characteristics. Often used 

interchangeably with the term “record.” 

Ecological indicators A subset of the physical, chemical, and biological elements and 

processes of natural systems selected to represent the overall health or condition of the 

system. 

Entity relationship diagram (ERD) A high-level data models that are useful in developing 

conceptual designs for databases. Creation of an ER diagram, which is one of the first steps 

in designing a database, helps the designer understand and specify components of a database 

and the relationships among those components. An ER model is a diagram containing 

entities, relationships among them, and attributes of the entities and the relationships. 

 

Information Created from data as a result of processing, manipulating, synthesizing, or 

organizing data in a way that provides interpretation or meaning. 
Appendix A A-3 

Inventories Extensive point-in-time effort to determine location or condition of a resource, 

including the presence, class, distribution, and status of plants, animals, and abiotic 

components such as water, soils, landforms, and climate. Inventories contribute to a 

statement of park resources, which is best described in relation to a standard condition such 

as the natural or unimpaired state. Inventories may involve both the compilation of existing 

information and the acquisition of new information. They may be relative either to a 

particular point in space (synoptic) or time (temporal). 

 

IRMA Integration of Resource Management Applications. The project name for the 

transition of multiple “silo” applications (e.g., NPSpecies, NatureBib, NPS Data Store) to a 

service-oriented architecture structure, which is being conducted by the NPS Natural 

Resource Program Center in Fort Collins. 

Logical data model (LDM) An abstract representation of a set of data entities and their 

relationships, usually including their key attributes. It may omit non-key attributes or use 

abstractions of actual types, and may include physical tables that are represented by 

relationships or as aggregates within a larger entity, depending on the notation used and the 

level of abstraction. The logical data model is intended to facilitate analysis of the function of 

the data design, and is not intended to be a full representation of the physical database. It is 

typically produced early in system design, and it is frequently a precursor to the physical data 

model that documents the actual implementation of the database. 

Master database Central repository for project data, used for viewing, summarizing, and 

analysis. Contains only data that have passed all quality assurance/quality control. 

Metadata Information about data. A metadata document contains specific and detailed 

information about a data set, including who, what, where, when, why and how the data were 

collected, analyzed, or manipulated. Metadata are considered an essential component of any 

good data set. 

Monitoring The collection and analysis of repeated observations or measurements to 

evaluate changes in condition and progress toward meeting a management objective. 

Detection of a change or trend may trigger a management action, or it may generate a new 

line of inquiry. Monitoring is often done by sampling the same sites over time, and these sites 

may be a subset of the sites sampled for the initial inventory. 

NatureBib The National Park Service bibliographic database, which is used to catalog, 

search, and manage natural resource-related information sources pertaining to national parks. 

National databases and repositories Applications and repositories maintained at the NPS 

national level, primarily for the purpose of integration among NPS units and for sharing 

information with cooperators and the public. 

Natural Resource Database Template (NRDT) is a core set of database tables that serves 

as a foundation for building relational databases for the NPS Inventory and Monitoring 

Program. 
Appendix A A-4 

Natural Resource Program Center (NRPC) The core of the NPS Natural Resource 

Stewardship and Science Directorate. NRPC staff are located in Fort Collins and Lakewood, 

Colorado, and in Washington, D.C. NRPC has five divisions: Air Resources; Biological 

Resources Management; Environmental Quality; Geologic Resources; and Water Resources. 

NRPC also includes the Office of Inventory, Monitoring and Evaluation; the Office of 

Education and Outreach; and the Office of Natural Resource Information Systems. 

Normalization The process of reducing a complex data structure into its simplest, most 

stable structure, thereby eliminating redundant attributes, keys and relationships. 

NPS Data Store An online graphical search interface that links dataset metadata to a 

searchable data server on which datasets are organized by NPS units, offices and programs.

NPS Data Clearinghouse – the central repository for NPS GIS data available to the public, 

implemented through the NPS Focus gateway. 

NPS Focus A decentralized digital imagery and data management system, implemented 

through a central Internet portal sponsored by the NPS Office of the Chief Information 

Officer. Includes to the NPS Data Clearinghouse. 

NPSpecies The master species database for NPS. The database lists the species that occur in 

or near each park, and the physical or written evidence for the occurrence of the species (e.g., 

references, vouchers, and observations). NPSpecies is implemented online through secure 

and public servers. 

NPSTORET The NPS version of the EPA (Environmental Protection Agency) STORET 

database, used for transferring water quality data collected by NPS programs to STORET. 

(see STORET) 

Physical data model A representation of a data design which takes into account the facilities 

and constraints of a given database management system. In the lifecycle of a project it is 

typically derived from a logical data model, though it may be reverse-engineered from a 

given database implementation. 

Protocols Highly detailed, formal documents that explain how data are to be collected, 

managed, analyzed and reported. Protocols are a key component of consistency and quality 

assurance for natural resource monitoring programs 

Relational Database Management System (RDMS or RDBMS) A system of storing data in 

related tables, which allows data to be structurally organized for maximum efficiency and a 

minimum of redundancy. 

Research Permit and Reporting System (RPRS) A web-based tool that provides a 

researcher with applications, procedures, and guidelines for submitting and obtaining a 

scientific research and collecting permit within NPS units. RPRS also includes Investigator 

Annual Reports, a report required by all receiving a permit. 
Appendix A A-5 

Sensitive data Any information which, through loss, unauthorized access, or modification 

could adversely affect a park resource or program, or the privacy of individuals. 

Service-oriented architecture A software architecture that modularizes business functions 

and allows different applications to easily share and exchange data. SOA separates functions 

into distinct services, which can be shared, combined, and reused to create applications. 

NRPC is transitioning many natural resource-related applications to SOA, which is an 

alternative to previous “silo” application architecture. 

Spatial data Information about the location, shape, and relationships among geographic 

features, usually stored as coordinates and topology. Can be stored in tabular or GIS file 

format. 

Standard Operating Procedures (SOPs) Detailed step-by-step instructions that outline a 

formal set of procedures for performing specific tasks. 

STORET (STORage and RETrieval) A database application maintained by the U.S. 

Environmental Protection Agency that contains raw biological, chemical and physical data 

on surface and ground water quality collected by federal, state and local agencies, Indian 

Tribes, volunteer groups, academics, and others. (see NPSTORET) 

Structured Query Language (SQL) A language used to query and process data in a 

relational database. All database systems designed for client/server environments support 

SQL. 

Vital Signs Ecological elements or processes chosen to represent the overall health or 

condition of park ecosystems, known or hypothesized effects of environmental stressors, or 

elements of value to humans, and are the subject of long-term monitoring by the Inventory & 

Monitoring Program. 

Working database – A project-specific database for entering and processing data for the 

current season (or other logical period of time). May also constitute the master database for 

short-term projects 
Appendix A A-6 
Appendix B B-1 

Appendix B. List of Acronyms 

Acronym Definition 

ANCS+ Automated National Catalog System 

CDM Conceptual Data Model 

CESU Cooperative Ecosystems Studies Unit 

CSDGM Concept Standards for Digital Geospatial Metadata 

DMP Data Management Plan 

EPA U.S. Environmental Protection Agency 

ERD Entity Relationship Diagram 

ESRI Environmental Systems Research Institute 

FGDC Federal Geographic Data Committee 

FOIA Freedom of Information Act 

FTP File Transfer Protocol 

GIS Geographic Information System 

GPS Global Positioning System 

HTML Hypertext Markup Language 

I&M Inventory & Monitoring (Program) 

IMS Internet Map Server 

IAR Investigator’s Annual Report 

IRMA Integration of Resource Management Applications 

IT Information Technology 

ITIS Integrated Taxonomic Information System 

JPEG Joint Photographic Experts Group 

LAN Local Area Network 

LDM Logical Data Model 

LiDAR Light Detection and Ranging 

MOU Memorandum of Understanding 

mp Metadata Parser 

MS Microsoft 

NBII National Biological Inventory Infrastructure 

NOAA National Oceanic and Atmospheric Administration 

NPS National Park Service 

NRDT Natural Resource Database Template 
Appendix B B-2 

Acronym Definition 

NRPC Natural Resource Program Center 

NRTS Natural Resource Table Standards 

OMB Office of Management and Budget 

PC Personal Computer 

PDA Portable Digital Assistant 

PDF Adobe Portable Document Format 

PDM Physical Data Model 

QA/QC Quality Assurance/Quality Control 

RDMS/RDBMS Relational Database Management System 

RFID Radio Frequency Identification 

SDE Spatial Database Engine 

SOA Service-oriented Architecture 

SOP Standard Operating Procedure 

SQL Structured Query Language 

TIFF Tagged Image File Format 

TSN Taxonomic Serial Number 

USGS U.S. Geological Survey 

WAN Wide Area Network 

WASO Washington Support Office 

XML Extensible Markup Language 
Appendix C C-1 

Appendix C. Checklist for completing or updating networklevel data management plans 

The following checklist originated as a series of questions used by peer reviewers to evaluate 

draft data management plans. The checklist was adapted for network-level data management 

plans in 2008. Networks should evaluate their plans against the elements in this list to ensure 

that all are addressed. 

#  Description 

Organization and Presentation 

1 The document is well-organized, clearly written, and professionally-presented. It 

has been reviewed by at least two persons other than the author before final 

submission. 

2 The Table of Contents includes a list of tables, a list of figures, and a complete 

list of appendices or supporting documents. 

3 An Executive Summary provides a concise overview of the plan, suitable for a 

non-technical reader. 

4 The plan includes (or provides URLs to) appendices, guidance documents, or 

SOPs for specific details on procedures or standards referenced in the plan. If 

all associated materials are not submitted with the plan, it is clear when and 

where they will be provided. 

5 All references mentioned in the plan are included in a Literature Cited section. 

6 A map showing the network location and network parks is included in the plan. 

7 A revision history log is included as part of the plan document. 

8 The scope and purpose of the plan is described, as well as how it functions in 

conjunction with the national data management plan, the network monitoring 

plan, and network-specific guidelines and SOPs.

Content 

While the following topics are broadly addressed in the national plan, the network plan 

should provide greater specificity than the national plan, and describes any items or 

procedures that diverge from the national plan. 

9 Data management-related staff roles and responsibilities are defined and 

explained. 

10 The network IT infrastructure supporting data management functions is 

described and clearly presented. 

11 The document provides file naming conventions and a network directory 

structure. 

12 There is a clear process for data mining at network parks, and for integrating 

this information into NPS-wide applications (NatureBib, NPSpecies, NPS Data 

Store). 

13 The acquisition, management, and integration of spatial data are described. 
Appendix C C-2 

#  Description 

14 There is a clear process for managing data resulting from inventory and 

monitoring projects, and integrating data into NPS-wide applications and 

programs (e.g., NatureBib, NPSpecies, NPS Data Store, NPS museum 

management). 

15 Procedures for managing photographs (digital and hard-copy) are presented 

and described. 

16 Projects and project management standards and procedures are defined and 

related to the management of information throughout the project life-cycle. 

17 There is a clear process for how the Natural Resource Database Template is 

used in the development of network-level inventory or monitoring databases. 

18 Quality assurance and quality control guidelines are provided for data collection 

and data entry. It is clear in the plan who is responsible for QA/QC, verification, 

and validation of network data. 

19 The plan specifies data documentation processes and tools that will ensure that 

metadata are comprehensive and developed in compliance with standards. 

20 Version control systems are documented for monitoring protocols, associated 

databases, and other documents or applications as needed. 

21 The general procedures for data analysis and reporting are explained in 

sufficient detail. 

22 Network internet and intranet website structure, content, and management is 

described and documented. 

23 Electronic data storage and backup procedures are clearly described, sufficient 

to protect all network data, and include provisions for off-site rotation of data. 

24 Filing and archive systems are sufficient to protect all network documents, and 

include integration with park or regional museum management programs. 

25 Implementation of the plan is described. Checks and balances are presented 

that will ensure, in subsequent years, that plan requirements are being met. The 

procedure for updating the plan is described. 
 

The Department of Interior protects and manages the nation’s natural resources and cultural heritage; provides scientific and other 

information about thos resources; and honors its special responsibilities to American Indians, Alaska Natives, and affiliated Island 

Communities 

NPS D-1968, May 2008. 
 

National Park Service 

U.S. Department of the Interior 

Natural Resource Program Center 

1201 Oakridge Drive, Suite 150 

Fort Collins, CO 80525 

www.nature.nps.gov 

 

EXPERIENCE YOUR AMERICA TM