Cover Sheet

Tracey Erwin

Geospatial Librarian

Branner Earth Sciences Library and Map Collections

397 Panama Mall; MC/2211

Stanford University

Stanford, CA 94305

650-725-1103

[terwin@stanford.edu](../terwin@stanford.edu)

Julie Sweetkind-Singer

Head Librarian, GIS & Map Librarian

Branner Earth Sciences Library & Map Collections

397 Panama Mall; MC/2211

Stanford University

Stanford, CA 94305

650-725-1102 (phone)

[sweetkind@stanford.edu](../sweetkind@stanford.edu)

Mary Lynette Larsgaard

Director, Map Library

Assistant Head, Map and Imagery Laboratory Davidson Library University
of California, Santa Barbara Santa Barbara CA 93106-9010

[http://www.sdc.ucsb.edu](http://www.sdc.ucsb.edu/)

805/893-4049; 2779 (phone)

[mary@library.ucsb.edu](../mary@library.ucsb.edu)

BIOGRAPHIES

Tracey Erwin is a Geospatial Librarian for the National Geospatial
Digital Archive (NGDA), a grant-funded project of the University of
California at Santa Barbara and Stanford University. The NGDA is a
collaborative initiative funded by the Library of Congress to identify,
collect, and preserve geospatial digital materials within a nationwide
digital preservation infrastructure. Tracey has worked on collection
development, selection and acquisition of data and imagery, and legal
agreements for the Archive since 2005.

Julie Sweetkind-Singer is the Head Librarian at the Branner Earth
Sciences Library and Map Collections at Stanford University. Her subject
specialization is maps and GIS. She is currently Stanford's project lead
on an NDIIPP grant from the Library of Congress. She has worked at
Stanford since May 2000. In 1999 she worked jointly with David Rumsey on
the Rumsey Map Collection Web site, which displays over 12,000 maps from
the eighteenth and nineteenth centuries. She was the President of the
Western Association of Map Libraries from June 2004 to July 2005. She
was the Vice-President of the California Map Society, Northern Chapter,
in 2001 and 2002. She received her M.L.I.S. from San Jose State
University and M.B.A. from the University of Colorado at Boulder.

Mary Lynette Larsgaard is the Director of the Davidson Map Library at
the University of California at Santa Barbara. Also, she has been
Assistant Head of the Map and Imagery Laboratory, Davidson Library,
since 1988. The Map and Imagery Lab has a collection of remote-sensing
imagery and maps of approximately 5.5 million items and is the largest
of its kind in any university library in North America. Larsgaard has
published extensively in the field of geospatial data in libraries, most
notably with a widely used text, Map Librarianship: An Introduction (now
in a third edition, published in 1998 by Libraries Unlimited); she is
also a coeditor (with Paige Andrew) of the Journal of Map and Geography
Libraries/Geoscapes. Her specialties are cataloging/metadata creation
and twentieth-century and more recent topographic and geologic maps. In
the year 2000 she was promoted to Librarian, Distinguished Step, a
promotion given only to librarians who have demonstrated superior
competence and are internationally recognized as an authority in an area
of library science.

ABSTRACT:

[The National Geospatial Digital Archive - Collection Development:
lessons learns]{.underline}

There are many similarities between building a geospatial digital
archive and building a hard-copy map collection, and two major ones are
the necessity to have a collection development policy and the amount of
hard work required to seek out and acquire the resources. It was clear
from the start that both National Geospatial Digital Archives partners
would have to collect digital data that was in line with each library\'s
standard collection strengths and responsibilities. Collection
development policies were written for the project as a whole and for
each partner institution. While based on traditional paper map policies,
these geospatial collection development policies are tailored
specifically for digital data by including sections on metadata,
versioning, file formats, proprietary formats, data set size, and
ownership/access considerations.

During the acquisition phase of the contract, a considerable amount has
been learned about file formats, data acquisition of compressed vs.
uncompressed files, short-term storage prior to repository ingest, and
metadata creation. While metadata creation at the
collection-level/series-level has been relatively easy, the acquisition
phase has underscored the challenges inherent in creating accurate
item-level metadata. The need to understand file formats and
specifications has lead to the creation of a format registry
specifically for geospatial materials.

INTRODUCTION:

The Library of Congress's National Digital Information Infrastructure
and Preservation Program's (NDIIPP) ambitious goal of collecting and
preserving our nation\'s digital heritage has been underway for over
four years. The results of the collecting efforts continue to emerge.
NDIIPP contracts were awarded to two projects focused on geospatial data
and imagery. Geospatial data represents a vast array of knowledge about
the earth ranging from highly accurate information about elevation, land
cover, glacial extent, sea surface temperatures, air and water quality,
to road and other infrastructure networks. Geospatial datasets combined
with visualization software allow for complex analysis of data about
place. Many disciplines use geospatial data to discern what is happening
on our planet and to predict possible future scenarios. Preserving a
part of this rich data is the mandate of the National Geospatial Digital
Archive (NGDA).

The University of California at Santa Barbara (UCSB), in partnership
with Stanford University (Stanford), was awarded an NDIIPP contract in
October, 2004. The mission of the NGDA is to \"collect and archive major
segments of at-risk digital geospatial data and images.\" The breadth
and quantity of geospatial data and imagery available today necessitates
judicious selection. For that reason, and from early conversations about
collecting, it was clear that formal collection development policies
would be vital to guide the process. With a few key collections in mind
at the project\'s inception, work began early in the contract period to
create collection development policies that would address both the
national nature of the NGDA, and the institutional realities of the two
universities hosting the archive. This resulted in the creation of three
collection development policies. The first is an overarching policy that
would guide any collecting body that signed onto the NGDA as a node. The
second and third are specific policies written for the founding nodes,
UCSB and Stanford.

**The Collection Development Policies**

The first policy to be written governs the collection efforts of the
NGDA as a whole. It is intended to serve as both a collection
development policy (CDP) in its own right for all of the NGDA nodes and
as a model for institutions who wish to develop their own geospatial
collection development policy. At the beginning of the contract period a
number of map libraries were surveyed about their geospatial collections
in order to discover what kind of collecting policies were in place for
such materials. A number of libraries indicated that although their
geospatial holdings were increasing, it was in an ad hoc manner, without
a systematic collecting policy. The NGDA policy is attached as Appendix
A of this article while the individual policies for UCSB and Stanford,
can be found on the NGDA website at <http://www.ngda.org/research.php>.

Digital geospatial collection activities at the two NGDA partner
institutions follow the research interests and institutional needs of
each respective institution. The amount of geospatial data and imagery
produced in the United States each year is vast, requiring both
institutions to make judicious choices about what to collect and the
frequency with which it will be captured. These institution specific
CDPs share some features and depart in some areas from the traditional
paper collecting policies upon which they are based.

The major similarities between each institution\'s digital geospatial
collection development policy and the collection development policy for
its paper collection are in the areas of subject, scope and region of
coverage. While the overarching policy suggests certain parameters, each
institution interprets the general guidelines differently to fit local
needs. Much longer sections on the scope of coverage are included
explicating how one would choose the type and scale of data to be
collected. Suggestions are included about where to go to get the
information once the type of data is chosen. For example, layers from
the National Atlas and the National Map that are relevant for a
particular institution are suggested. In the case of Stanford, with its
strong focus on earth sciences, ten National Atlas layers were chosen
for downloading focusing on volcanoes, historical earthquake data,
bathymetry, geologic fault and seismic hazard layers.

Each institution\'s geospatial CDP parallels the traditional focus of
the respective university. UCSB\'s collection has always focused on
southern California, and includes its prominent aerial photography and
imagery collection. Stanford has always had an emphasis on Northern
California, the San Francisco Bay Area and the Monterey Bay. Figure 1
below, illustrates some of the notable similarities and differences in
collecting scope at UCSB and Stanford University.

+-----------------------------------+-----------------------------------+
| ### UCSB CDP                      | ### STANFORD CDP                  |
+-----------------------------------+-----------------------------------+
| ### A.                            | ### A. Geography Pri              |
|  Geography Primary collecting emp | mary collecting emphasis is on th |
| hasis is on the geographic area f | e geographic area firstly of Sant |
| irstly of Santa Barbara County, a | a Clara and San Mateo Counties, a |
| nd of California as a whole, and  | nd of California as a whole, and  |
| secondarily of the United States. | secondarily of the United States. |
+-----------------------------------+-----------------------------------+
| ### B. Subject Pote               | ### B. Subject Pote               |
| ntial types of materials are spli | ntial types of materials are spli |
| t across physical and human/cultu | t across physical and human/cultu |
| ral geography. The list has been  | ral geography. The list has been  |
| derived from the Library of Congr | derived from the Library of Congr |
| ess G Schedule and then modified. | ess G Schedule and then modified. |
+-----------------------------------+-----------------------------------+
| ###                               | -   For Santa Clara and San Mateo |
|  For Santa Barbara County, UCSB w |     Counties, Branner will        |
| ill collect all subjects listed.  |     collect all subjects listed.  |
|                                   |                                   |
| ###  For C                        | -   For California as a whole,    |
| alifornia as a whole, UCSB will c |     Branner will concentrate on   |
| oncentrate on the following subje |     the following subjects:\      |
| cts: topography biogeography exce |     topography\                   |
| ption: agriculture, which is UC D |     geology\                      |
| avis\' purview within the UC Libr |     environmental aspects of such |
| aries system historical geography |     areas as oceanography,        |
|                                   |     climatology, economics, etc.  |
| ###                               |                                   |
|                                   | i\. Map-format materials (e.g.,   |
| ###                               | maps, diagrams, sections, views,  |
|                                   | profiles)                         |
| i\. Map-format materials (e.g.,   |                                   |
| maps, diagrams, sections, views,  | -   [a. Physical                  |
| profiles)                         |     geography]{.underline}\       |
|                                   |     - Mathematical geography      |
| ###                               |     (surveying and cartography;   |
|                                   |     etc.)\                        |
| ### [a                            |     - Physiography (e.g.,         |
| . Physical geography]{.underline} |     topography, bathymetry and    |
|  - Mathematical geography (survey |     hydrography including         |
| ing and cartography; etc.) - Phys |     nautical charts)\             |
| iography (e.g., topography, bathy |     - Hydrology\                  |
| metry and hydrography including n |     - Geology, geophysics,        |
| autical charts) - Hydrology - Geo |     mineral resources, and soils\ |
| logy, geophysics, mineral resourc |     - Climatology\                |
| es, and soils - Climatology - Bio |     - Biogeography (land use/land |
| geography (land use/land cover)   |     cover)                        |
+-----------------------------------+-----------------------------------+
| ### [b. Human and cul             | ### [b. Human and cul             |
| tural geography]{.underline} - Po | tural geography]{.underline} - Po |
| litical geography - Public lands; | litical geography - Public lands; |
|  ethnic reservations - Demography |  ethnic reservations - Demography |
| ; census - Transportation and com | ; census - Transportation and com |
| munication - Historical geography | munication - Historical geography |
+-----------------------------------+-----------------------------------+

Map-format materials (e.g., maps, diagrams, sections, views, profiles)

Geospatial collection policies for both universities differ from their
paper policy counterparts in many ways. First, the potential patrons
extend far beyond the usual university scope of students, faculty and
staff to include all citizens of the United States, present and future.
As a project funded and supported by the Library of Congress the NGDA\'s
mandate includes potential patrons who are substantially the same as
those who might use the Library of Congress itself. This does allow
greater latitude in collecting as the potential patron base is so broad;
anyone who might potentially benefit from these collections is included.
While that might seem like carte blanche to collect broadly, both
libraries follow their CDP's closely to ensure research level
collections in their areas of focus. A number of elements set these
digital geospatial collection policies apart from their analog brethren.
In addition to sections on subject, scope and area of coverage, digital
geospatial CDPs also address metadata, format, versioning, proprietary
formats, data set size, and ownership/access considerations.

Metadata - Unlike analog materials, such as books, where an item\'s
metadata travels with it in the form of title pages, or maps, where the
margins contain legends, titles, publication data, and the like, digital
data sets may not carry their own metadata. Such information often
travels in an accompanying file. Ensuring that this data is captured is
therefore critical to archiving digital datasets. Such metadata is vital
for understanding the purpose of a particular data set, and includes
when it was created, by whom it was created, technical information of
interest to researchers such as the equipment (sensors, lens, settings)
that created the data, and copyright information. Metadata regarding
format may also be important for extracting data from an archive.
Knowledge of the format in which the data was created is necessary for
re-constituting it in order to view and utilize it, or migrate it to the
next generation of software. Although there are standards for geospatial
metadata creation, such as the Federal Geospatial Digital Clearinghouse
(FGDC) standard, and ISO 19115:2003, not all data producers adhere to
the recommended elements and the lack of uniform metadata is rampant.
This lack uniformity has ramifications for archiving geospatial data
generally. Boxall (2004), noted the absence of standard procedures for
archiving geospatial information and suggested that librarians work
toward developing geospatial archiving standards. In 2008 standardized
archiving procedures for geospatial data continue to be emerging rather
than established.

Format - All digital data is created in a given format and this has
implications for collecting and archiving. The CDPs for both UCSB and
Stanford address the preference for obtaining data in open formats as
well as the reality that a great deal of geospatial data is produced in
proprietary formats. Thus both proprietary and open source formats are
archived. It should be noted that neither node of the NGDA is archiving
software.

Versioning -- Analogous to paper map products, much digital geospatial
data and imagery is produced at regular intervals to capture change over
time. The collection policy addresses the need to collect at appropriate
intervals to ensure holding both current and historical data. In the
date/chronology section, the need for versioning is discussed as the
decisions about when to collect content has shifted to the librarian and
away from the content producers. Librarians and others charged with
decision making must assess appropriate intervals for data collection.
This will vary, of course, depending on the nature of the data being
collected. The NGDA CDP describes issues that impact decisions regarding
when and how often to collect including:

• new releases of data sets by the publisher when changes occur;

• trigger events such as the decennial census, or single events such as
the aftermath of natural disasters;

• seasonal changes in the case of collecting Landsat scenes;

• changes in boundary lines such as school district or electoral
districts;

• urban or infrastructure growth that impacts transportation routes or
other observable features.

Proprietary formats - Proprietary formats that are widely used are
archived in both NGDA nodes. When ingested into the Stanford Digital
Repository, the formats are described as fully as possible in a transfer
manifest, essentially a digital packing slip that tells the repository
what it is receiving. Similarly, at UCSB proprietary formats are
archived with a notation in the metadata that the format is proprietary.
There is some concern over archiving proprietary formats. The central
premise of the NGDA model for archiving is that format information is
essential to the long-term value of any particular object. However, as
proprietary formats are common for geospatial data, archives will have
to make decisions about how to provide access to these data in the
future. While the archives can preserve the data now, for future users
to view and utilize the data may require that they have access to
software to convert data from a previous format to the current format of
the day. Format migration has been discussed by the nodes as a possible
solution. It has not been tried on geospatial files and will be
considered on a case-by-case basis for each format in the future. Other
agreements, yet to be negotiated with the creators of proprietary
formats, could also enable the future use of such data.

Data set size and ownership/access considerations - Geospatial data sets
can be quite large. For some public domain data direct downloading is a
possibility, however it is so labor intensive as to be prohibitive. As
an example of data set size, the Stanford NGDA repository obtained data
from the United States Geological Survey (USGS) for a relatively modest
area of California and Nevada. Three sets of data, comprised of parts of
the National Elevation Dataset (NED), the National Agriculture Imagery
Program (NAIP) dataset, and high resolution orthoimagery for the
Monterey Peninsula constituted 571 gigabytes of data. As public domain
datasets, access considerations due to copyright or licensing
restrictions are not a concern. The NGDA repositories are not intended
to be dark archives. Although scenarios can be envisioned in which there
would be a temporary moratorium on access, this would not be ideal. In
any case, even if materials were archived but not available to the
public, discovery of the materials would be provided for as well as
information on how to obtain the data from the originating source.

One instance of ownership/access issues that the NGDA has encountered
pertains to the California Geological Survey (CGS). There are serious
access implications for many governmental agencies if they are funded
according to how much the agency and its website are used. For example,
the CGS has agreed to have the library at the University of California,
Santa Barbara archive its digital data. However, the agreement included
the provision that it is essential that the UCSB library point its users
of CGS data to the CGS website, to maximize that website\'s use. Direct
access through UCSB will be allowed when the CGS website is not
available.

Risk - Perhaps data most at risk are those created by institutes,
individuals, and small research centers that lack institutional
resources to do their own archiving. Such entities will need to be
approached thoughtfully to discuss the need for long term preservation
of their work and to decide if a large university archive is the proper
place to house their content. Legal agreements have been written by the
NGDA partners that govern the rights and responsibilities of the content
depositors and the archives in order to create a climate of openness and
trust.

**II. Identification and Acquisition of Resources**

**Lessons of acquisition**

The ongoing work of the NGDA continues to yield valuable technical and
non-technical experience. The most significant areas where hands-on
experience has resulted in new knowledge are metadata creation,
acquisition of data, format issues and storage of data.

[Metadata Creation]{.underline} - One of issues that stewards of digital
collections grapple with is the variability of metadata. Not only is it
the case that not all collections have good metadata, many have no
metadata at all; and metadata creation, like the creation of standard
catalog records, is an extremely time-consuming and therefore expensive
activity. When faced with a situation where metadata is less than
optimal choices include creating metadata where possible, choosing not
to archive the data at all, or archiving with limited metadata while
explaining to the depositor that less metadata may lead to less utility
for the data in the future.

For example, the NGDA acquired a bundled variety of data and imagery
accompanied by less than ideal metadata from a third party data
aggregator. All of the data are in the public domain. The company added
value to existing data by georectifying the images and digitizing
features. The data included national shoreline and boundary data,
military vector data, and Shuttle Radar Topography Mission data. The
data was delivered with descriptive metadata and lacked any technical
descriptions. After examining the company website and contacting
customer service it was learned that all the metadata they had had been
delivered. If possible, further metadata would need to be obtained from
the government entities that originally created the data.

At times, metadata will be provided at both the collection level and at
the individual level. For example, part of the NGDA content is the
Landsat 7 images for the state of California and part of Arizona. This
set (a subset of a worldwide collection of Landsat 7 imagery) contains
38 scenes. Included with the metadata is information that is the same no
matter which image is being viewed (such as the format, information
about the satellite, the naming conventions for the scene and the bands,
contact information, etc.). Also included with each image is the
metadata related to each specific scene (such as the scene ID, the path
and row numbers, and the date of acquisition). One then must decide how
to store the collection and individual metadata for each item. The
collection and individual information is retrievable for each item in
the collection.

One collection that has presented interesting metadata challenges is the
David Rumsey Map Collection. Individual cataloging records have been
created for nearly all of the items in the collection, but upon closer
inspection, it was found that numerous images had no corresponding
metadata, requiring individual reconciliation of each item with the best
possible metadata record. This happened most frequently with atlases
where there were images of the maps, the covers, the title page, and
other text pages. The maps were automatically associated with the images
by a corresponding file name and metadata field. The extra imagery
(covers, title pages, text) had no such corresponding file name in the
associated metadata, requiring inspection of each item that failed to
have matching fields. These records were inspected by hand and were
associated to the main cataloging record that described the whole atlas.
Even with excellent metadata records, the way in which the cataloging
was done created idiosyncrasies when adding the images to the repository
that did not allow for automated ingest of the whole collection.

[Acquisition issues for compressed or converted files]{.underline} -
Much geospatial data is available for download in compressed formats.
While this speeds download time and reduces storage requirements, for
long term archiving the native format is preferable. Storing files in
their uncompressed original form is standard archiving protocol as
compression can lead to bit loss. Compressed files also require another
layer of quality control as they must be uncompressed to check that data
is intact for archiving. While files being downloaded include geotifs,
shapefiles, .dbf and export files, many files being acquired for the
archive have been converted into a transfer format. Numerous layers of
the National Atlas, for example, are downloaded in a format called
Spatial Data Transfer Standard (SDTS). Similar to compressed file in
that they are one-step removed from their original format, SDTS files
may require validation prior to ingest into the repository.

Another step in readying data for ingest into an archive is creating a
file structure and naming conventions to keep track of the data in
whatever temporary staging location holds the data. The data and imagery
files are checked for completeness and readability to ensure the files
were not corrupted at some point in the process of creation or
collection. Additional steps like these to verify the validity of data
and organize it add labor time to the archive process and are an
archiving cost that might not be obvious at the outset.

[Format Issues]{.underline} - As discussed earlier, digital geospatial
data is created in a number of different formats. Some geospatial
formats, such as ESRI\'s shapefile, consist of multiple files that
constitute one digital object and must travel together. This adds a
layer of complexity when attempting to archive such files. This
complexity was part of the impetus for creating a geospatial format
registry. The goal of the format registry is to accurately and
thoroughly describe as many of the formats as possible that are
collected by the NGDA. Through description of the formats in a central
location, all individual files can point to that information rather than
having to pack it in its own metadata file. Registries of this sort
typically include information about the nature of the object, the format
creator, version information, and documentation written about the
format. Understanding the formats in this way increases the likelihood
of preservation in the future as they inevitably become obsolete.

The NGDA format registry is in its beginning stages with work presently
focusing on the emerging standards across the field including comparison
of models being set up by the Global Digital Format Registry (GDFR) and
PRONOM. These registries have not been built out for geospatial formats
hence the need to build out the existing models with relevant fields for
these types of data and imagery. Five initial formats are being built
out including ESRI's shapefiles, ESRI's ArcINFO GRIDs, .tif and geotifs,
BIL and HDF files. Shapefiles are commonly used and examples from our
collections include National Atlas and National Park Service layers as
well as layers from the California Spatial Information Library (CASIL).
Tif and geotif are typically image formats including the NAIP of the
California Bay Area. The SRTM topographic data is in .bil format. ASTER
and MODIS imagery, often used for land cover analysis, is delivered in
the .hdf format. It is hoped that by the end of the contract the
registry will have information about all formats held by the NGDA.

[Ingest and Short Term Storage]{.underline} - Geospatial data that are
selected for archiving go through a multi-step process prior to ingest.
After a collection is identified it may be downloaded from its original
location, or received on a storage media such as an external hard drive.
It is then uploaded to a temporary storage location. At Stanford this is
network attached storage (NAS). A protocol for incoming datasets has
been developed. In order to track data from arrival, to storage, to
archive Stanford starts by creating a log, or manifest of the files upon
receipt. An open source application called MD5 Deep is used. MD5 Deep
walks through one directory at a time creating digests of each file
found, and goes through any subdirectories found. This \"snapshot\" of
the data upon arrival is a safeguard that allows for detection of any
future change or loss of files prior to ingest. The next step is mapping
all descriptive metadata into MODS (Metadata Object Description Schema).
Then a transfer manifest is created as described earlier, and this
\"packing slip\" tells the repository what is being received. If no
issues emerge during these stages, a sample item is ingested. If the
test is successful, ingest of the full collection begins.

At UCSB the process is similar. The archive brings in data in a series
of steps. Once a collection is identified as at-risk or otherwise
desirable for preservation, the archive transfers it to local storage.
Reliable transfer methods, such as Rsync (a robust internet file
transfer tool), are used to ensure that the entirety of the dataset is
received. In the case of extremely large datasets, or if a collection
holder has an unreliable network connection, physical media may be
transferred. Once the transfer has been completed, the data is ready to
be worked with, but is not yet in the archive.

Before the data can be ingested into the archive, preliminary work must
be done. Collections and sub-collections are identified, and when
applicable, templates are created. Templates describe the structure of
data within a (mostly) homogeneous collection. Once a collection is well
understood and defined, the ingest processing begins. Configuration
files are used to map disparate components into structured Archive
Objects. Workflow tools allow for quality control prior to any
interaction with the archive. When all checks are satisfied, Archive
Objects are created, data are copied, and items are considered archived.

CONCLUSION:

Collection development for a digital geospatial archive is complex,
labor intensive and challenging. The NGDA nodes have worked to create a
systematic process for selection, capture, and archiving. This has
required close collaboration between the collections librarians and the
digital archivists, including metadata specialists and programmers. The
value of building such collections as we move forward in the digital age
is significant and insures that part of the considerable geospatial data
output of the nation is being captured for future use. Those responsible
for collection development need to work closely with their technical
counterparts in archive building to understand metadata requirements,
short-term storage options and any other factors that will impact the
ultimate goal of acquiring geospatial data and imagery. The size of
geospatial datasets will require cooperative strategies among libraries
and other archiving entities to ensure replication, but not needless
duplication, of materials. The NDIIPP program provided the necessary
funding and impetus to tackle long-term preservation at UCSB and
Stanford for geospatial materials, creating a partnership that will
continue long into the future.

\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\--

^i^ The transfer manifest is an information package per the description
of the Open Archive Information System (OAIS) reference model released
in May 1999. When information about the content object and its metadata
are aggregated for purposes of ingestion into the Stanford Digital
Repository, the transfer manifest or TM could be considered a SIP or
Submission Information Package minus the actual inclusion of the content
files themselves.

^i\ i^ The USGS offers this definition of SDTS: \"The Spatial Data
Transfer Standard, or SDTS, is a robust way of transferring
earth-referenced spatial data between dissimilar computer systems with
the potential for no information loss. It is a transfer standard that
embraces the philosophy of self-contained transfers, i.e. spatial data,
attribute, georeferencing, data quality report, data dictionary, and
other supporting metadata all included in the transfer.\"

<http://mcmcweb.er.usgs.gov/sdts/whatsdts.html>

WORKS CITED

Ahonen-Rainio, P. (2005). Metadata for Geographic Information.

> *Journal of Map and Geography Libraries, 2* (1), 37-65.

Author Unknown (Aug 24, 2005) *Birthplace of the DOQ -- USGS Western
Region*. Retrieved June 23, 2008 from
<http://online.wr.usgs.gov/ngpo/doq/>

Author Unknown (Sept 11, 2003) *What is SDTS?* Retrieved June 23, 2008
from <http://mcmcweb.er.usgs.gov/sdts/whatsdts.html>

Boxall, J. (2004). Advances and Trends in Geospatial Information
Accessibility-Part I: Geolibraries. *Journal of Map and Geography
Libraries, 1* (1), 7- 39.

Cornell University Geospatial Information Repository (Aug 25, 2006).
*Cugir: Collection Development Policy - Cornell University Geospatial
Information Repository.* Retrieved June 24, 2008 from
<http://cugir.mannlib.cornell.edu/CUGIRCollectionDevtPolicy_20060825.pdf>

Federal Geographic Data Committee (2008). *Content Standard for Digital
Geospatial Metadata (CSDGM) Essential Metadata Elements.* Retrieved June
24, 2008 from
<http://www.fgdc.gov/metadata/documents/CSDGMEssentialMeta_20080514.pdf>

Hoebelheinrich, N. (2008) *Metadata for Stanford Digital Repository*.
Retrieved June 30, 2008 from
<https://consul.stanford.edu/display/DLMD/Metadata+for+Stanford+Digital+Repository>

Research Libraries Group, Inc. (2002). *Trusted digital repositories:
Attributes and responsibilities,an RLG-OCLC report.* Retrieved May 21,
2008, from
http://www.oclc.org/programs/ourwork/past/trustedrep/repositories.pdf

Steinhart, G. (2006). Libraries as Distributors of Geospatial Data: Data
Management Policies as Tools for Managing Partnerships*. Library Trends,
55* (2), 264-284.

Sweetkind-Singer, J., Larsgaard, M., Erwin, T. (2006). Digital
Preservation of Geospatial Data. *Library Trends, 55* (2), 304-314.

COLLECTION DEVELOPMENT POLICY FOR THE NATIONAL GEOSPATIAL DIGITAL
ARCHIVE\
Final Version - November 1, 2006

### I. Collection purpose and description of the users

The purposes of the NGDA collection are to archive broad collections of
digital geospatial data of the United States, and make it available to
users. The primary users of the NGDA are citizens - present and future -
of the United States of America. The secondary users of NGDA are all
other people who use the Web. Users of geospatial data are many; the
following brief list is a sampling:

-   From the university/academic world, undergraduate and graduate
    students and faculty, especially in those disciplines which deal
    with geographic areas, e.g., geography, anthropology, history, etc.;

-   From elementary and secondary schools, students and teachers looking
    for information about a specific country or city;

-   From the world of business and commerce, commercial vendors of
    imagery and mapping services; firms that need to know demographic
    information; realtors;

-   Non-profit, non-governmental organizations such as relief
    organizations; economic and social councils, etc.;

-   Persons and firms collecting information about the environment;

-   Government agencies - local, state, federal, international.

### II. Selection, Evaluation and Prioritization

Geospatial data are produced in large quantities from a wide-ranging
group of organizations and entities. Data producers include government
agencies, commercial vendors and individuals. It is important to
carefully evaluate the needs of the collecting institution in selecting
materials to collect and archive. In order to begin the process, the
following steps are recommended.

1\. Develop awareness of potential collections.

-   Contact and/or explore resources at local, regional, state, and
    federal agencies to find out what data are produced for the area of
    interest. Attend regional interest group meetings. Sign up for
    relevant e-lists such as GIS4lib and Maps-L. Read and subscribe to
    print and online publications focused on GIS data. Consider
    commercial sources for the area of interest.

2\. Check that a potential collection is within the Scope of Coverage
(see Section III below).\
3. Assign a priority rating to each potential collection using the
following questions as a starting point.

-   Is collection in scope for the NGDA and for the NGDA collecting
    institution?

-   Is the collection\'s geographic area of primary importance to the
    collecting institution?

-   Is the collection at risk due to either:

-   The content provider does not archive the content.

-   The file format is becoming obsolete.

4\. Obtain resources to collect first priority collections. Resources
include collection funds if the data are not free, metadata/cataloging
services, server or repository space, and resources to access the data
such as computers and relevant software.\
5. If resources are available, proceed to second priority collections.

### III. Scope of coverage

The scope of collecting is solely in the realm of geospatial digital
data. The term, \"digital geospatial data,\" is defined as digital
items, displayed as graphics, that are georeferenced or are
geographically identified. These are primarily composed of: digital
maps; remotely sensed images (e.g., aerial photographs; data collected
by satellite sensors); datasets (e.g. shapefiles, layers, geodatabases,
etc.); atlases; globes (celestial and terrestrial); aerial views (e.g.,
panoramas); block diagrams; geologic sections; topographic profiles;
etc.

A. Geography\
Primary collecting emphasis is on the geographic area of the United
States. Data may cover the entire United States including U.S.
territories; or data may be focused on a specific state, consortial area
(e.g., southern California; metropolitan New York City), county, city,
or city neighborhood.

i\. United States national or large regional extent\
Many subjects listed in Section B are available at a national level. For
example, the United States Census Bureau publishes datasets for the
geographic regions designated by their decennial census. National
datasets available through numerous national government agencies and
commercial entities cover many subjects and may be updated on a set
schedule, such as census data every 10 years. Some of these datasets may
be compiled in such a way to be of a manageable size for viewing, use,
and preservation. Examples would include numerous layers in the National
Atlas
([http://www.nationalatlas.gov/![](media/image1.png){width="7.291666666666667e-2in"
height="7.291666666666667e-2in"}](http://www.nationalatlas.gov/)).
Others are very large and may require special treatment for archive
consideration. For example, the United States Geological Survey produces
and continues to update the National Elevation Dataset, served through
the National Map
([http://www.nationalmap.gov/![](media/image1.png){width="7.291666666666667e-2in"
height="7.291666666666667e-2in"}](http://www.nationalmap.gov/)) website.
The full dataset, as of May 2006, is 60 gigabytes of data. It may be the
case at this point that such a dataset is too large for any one node to
archive and so should be split across a number of archives. As of Spring
2006, many national agencies producing geospatial data are working out
the policies for the archiving of their geospatial resources. Because
policies are still being created, it is recommended that important
datasets be archived at the local level to provide long-term access to
the material.

ii\. State, county, or city within the United States.\
Datasets at this level are often produced by state, county, or city
agencies. Coordination between groups often occurs because of the cost
to produce some of the more expensive datasets. For example, this may be
the case for aerial photography created at set intervals. Many states
have created geospatial clearinghouses for dissemination of popular
datasets. Preservation and retention of older datasets is not guaranteed
nor often spelled out at the clearinghouse sites. Basemap data at each
level are important to collect including transportation networks,
boundary files, water resources, parcel information, and agency-specific
data. Statewide clearinghouses are excellent sources for these data.
Counties and cities may disseminate their data over the Internet,
although it is highly likely one will need to contact these groups
directly. Copyright status should be ascertained when collecting data at
this level.

iii\. Ocean-floor coverage: off-shore areas to the limit of the United
States\' maritime boundary claim.\
Data of this type may include multi-beam surveys, sonar readings,
electronic nautical charts, and vector data delineating boundary claims.
It is created by national and state agencies, as well as academic
institutions and research institutes.

B. Subject\
Potential types of materials are split across physical and
human/cultural geography. The list has been derived from the Library of
Congress G Schedule and then modified.

i\. Physical geography

-   Mathematical geography (surveying and cartography; etc.)

-   Physiography (e.g., topography)

-   Hydrology

-   Oceanography

-   Rivers and lakes

-   Floods

-   Geology, geophysics, mineral resources, and soils

-   Climatology

-   Biogeography (land use/land cover)

-   Flora

    -   General

    -   Aquatic

-   Forests and forestry

-   Agriculture

-   Fauna

    -   General

    -   Aquatic

ii\. Human and cultural geography

-   Political geography

-   Economics

-   Real property; cadastre

-   Public lands; ethnic reservations

-   Demography; census

-   Technology; engineering; public works

-   Transportation and communication

-   Commerce and trade; finance

-   Military and naval geography

-   Historical geography

iii\. Remotely-sensed images

-   Aerial photographs

-   Satellite images

C. Date or Chronology\
Geospatial data is often subject to versioning. New versions of data
layers are released when changes occur in the original dataset. This can
be done to correct errors or to account for changes over time. Data may
be changed incrementally or on specific dates due to \"trigger-events,\"
such as the decennial census. Once it has been decided which datasets
are important to archive, a decision should be made about the frequency
with which versioning should occur. For example, Landsat imagery might
be collected once a quarter to follow seasonal changes. School district
lines may only need to be captured when boundaries are re-drawn.
Transportation routes could be updated on a yearly basis. Geospatial
data collected immediately after a natural disaster would be collected
as soon as it was made available to libraries and/or the public.

D. Format\
As part of the NGDA project, only digital materials are collected. The
digital data must be accompanied by minimum core required metadata.
Section IV covers metadata recommendations. Open source, non-proprietary
file formats that are either readily manipulated using standard
image-processing or geographic-information-system software are preferred
(e.g., geotiff, GML). Data in proprietary formats or data whose display
is dependent upon proprietary software (e.g., ArcInfo Coverage or GRID)
will be dealt with on a case-by-case basis. Some important factors will
be how commonly available and used the software is and whether the data
may be exported to a non-proprietary format. For example, the ESRI
shapefile is a proprietary format, but it is so universally used, the
current NGDA nodes will accept data in this format. Format registries
for geospatial data are presently being created to capture relevant
representational information about file formats. The Library of Congress
has posted the \"Sustainability of Digital Formats Planning for Library
of Congress Collections\" on their Web site
([http://www.digitalpreservation.gov/formats/intro/intro.shtml![](media/image1.png){width="7.291666666666667e-2in"
height="7.291666666666667e-2in"}](http://www.digitalpreservation.gov/formats/intro/intro.shtml)).
At present, it contains no information about geospatial file formats,
but certainly will in the future. The Global Digital Format Registry
(GDFR) is also interested in including geospatial format information
([http://hul.harvard.edu/gdfr/![](media/image1.png){width="7.291666666666667e-2in"
height="7.291666666666667e-2in"}](http://hul.harvard.edu/gdfr/)).
Appendix 2 includes definitions of some of the more common geospatial
data formats. File formats will change over time with new formats being
created and older formats falling into disuse. The Archives should
continually evaluate if it is possible to migrate older formats into
newer ones, decide when and if old formats will be kept, and keep
abreast of best practices in the geospatial community regarding file
formats.

E. Language\
English will be the most frequent language collected due to the nature
and focus of the grant; but it is possible that geographic coverage for
areas in the U.S. may have text portions in languages other than
English.

F. Copyright\
Materials without copyright - e.g., public domain data - comprise much
of the collection. Acquisition and access to copyrighted data will be
governed by an agreement between the NGDA collection node and the data
provider. Access to certain data may be restricted for a specified
period of time at the request of the data provider. The NGDA nodes do
not intend to be dark archives. G. Exclusions:

-   Digital information with a geographic reference, such as a text
    history of Alabama

-   Analog materials

-   Straight statistical data not tied to a geographic area

-   Data layers external to the United States

-   Data that is to remain perpetually \"dark\"

-   The HTML content from Web sites (Geospatial data gathered from Web
    sites will be collected.)

### IV. Metadata recommendations

It is important to collect as much metadata as is feasible. The NGDA
recommends a core set of metadata fields with the understanding that it
may not be available in all cases. Whether or not content lacking core
fields will be ingested into a node is up to the node itself.
Significant metadata in rough order of importance:

-   Geographic area: This includes information about the extent of the
    content. Specific node requirements could require coordinates in
    decimal degrees or words describing the extent (\"Arizona counties\"
    qualified by years).

-   Type (intellectual content): This includes maps, remote-sensing
    imagery (aerial photograph; image from satellite), layers.

-   Format: This should identify the file types included (e.g., tiff,
    jpeg, arcexport, shapefile).

-   Projection and/or coordinate system.

-   Scale and/or resolution. Resolution is often cited when dealing with
    aerial and satellite imagery.

-   Transfer media: This component details the device upon which the
    data are stored when deposited with the archive (CD-ROM, DVD-ROM,
    hard-drive, etc.).

-   Title: A title is required for each item ingested. A title may also
    be included for the whole collection.

-   Date of information: This would be the date the information was
    created.

-   Issuance information: This includes the issuing agency, the place of
    issuance, and date of issuance.

-   Data Quality information e.g. FGDC metadata elements such as
    attribute accuracy and completeness report.

-   Rights Information e.g. copyright, reproduction of data.

-   Date ingested into the archive.

-   Contact information for the content provider: This would potentially
    include a contact person(s), address, telephone/fax, email
    addresses, or Web site.

-   Collection name and description: This may be supplied by the node
    ingesting the data.

-   Controlled-list subject headings: This might be created by the
    content provider. Hopefully they would provide a full copy, but at
    the very least a full \"bibliographic\" citation.

-   Other fields: If content provider provides any fields, then they
    should also include the field name, field definition, and domain (an
    authority list).

### V. Sources for digital geospatial data

Although governmental sources of data are of primary interest, the
archive is not to be limited to data generated, or contracted, by
federal agencies of the United States, but instead will include digital
geospatial data generated by any agency or person. The emphasis will be
firstly on nationwide coverage, of any theme, and very often these are
generated by federal agencies. It is expected that nodes will collect in
this area according to their specific regional and research needs. This
may mean that part of the collecting decision is made by the scale of
the dataset.The NGDA nodes will focus on government agencies at all
levels and non-profit entities such as professional organizations or
environmentally focused non-profits, with a secondary focus on
commercial firms, and a tertiary focus on products issued by people.

### VI. Coordination and cooperation with other collections

The NGDA\'s mission is to be a collecting network. As such,
collaboration with other institutions is expected and necessary. Because
digital geospatial data sets require large amounts of server space, the
cooperation of many institutions will be necessary to build an extensive
collection. Cooperation agreements written specifically to govern the
collecting areas of the partners should include:

-   The collecting areas for each participating institution.

-   The frequency of updates and versioning for each dataset.

-   The length of the agreement.

-   The type and level of access to be provided to the collected
    materials.

-   A set interval to review the collection agreement.

-   A glossary.

### VII. Appendices

**Appendix 1:**

**Sample NGDA-node collection development policies**\
Note: Once this policy has been vetted and finalized, both UC Santa
Barbara and Stanford will write Collection Development Policies for
their nodes.

**Appendix 2: Glossary**

**Digital Elevation Model**\
Digital Elevation Models display a 3 dimension-like image of surface
elevation by using a raster grid of evenly spaced elevation values. The
values are obtained from USGS topographic maps.\
Compiled from multiple sources including:\
Retrieved June 10, 2006,
[http://edc.usgs.gov/products/elevation/dem.html![](media/image1.png){width="7.291666666666667e-2in"
height="7.291666666666667e-2in"}](http://edc.usgs.gov/products/elevation/dem.html)\
Retrieved June 10, 2006,
<http://www.landinfo.com/resources_dictionaryAD.htm#d>![](media/image1.png){width="7.291666666666667e-2in"
height="7.291666666666667e-2in"}

**Digital Orthophoto Quadrangle**\
A digital orthophoto quadrangle (DOQ) is a computer-generated
georeferenced image of an aerial photograph in which image displacement
caused by terrain relief and camera tilts has been removed. It combines
the image characteristics of a photograph with the geometric qualities
of a map.\
Retrieved June 9, 2006, from:
[http://www.usgsquads.com/prod_doqq.htm![](media/image1.png){width="7.291666666666667e-2in"
height="7.291666666666667e-2in"}](http://www.usgsquads.com/prod_doqq.htm)

**Digital Raster Graphic**\
A digital raster graphic (DRG) is a scanned image of a U.S. Geological
Survey (USGS) standard series topographic map, including all map collar
information. The image inside the map neatline is georeferenced to the
surface of the earth and fit to the Universal Transverse Mercator
projection. The horizontal positional accuracy and datum of the DRG
matches the accuracy and datum of the source map. The map is scanned at
a minimum resolution of 250 dots per inch.\
Retrieved June 9, 2006, from:
[http://topomaps.usgs.gov/drg/![](media/image1.png){width="7.291666666666667e-2in"
height="7.291666666666667e-2in"}](http://topomaps.usgs.gov/drg/)

**GML**\
GML is an acronym for Geography Markup Language. An OpenGIS
Implementation Specification designed to store and transport geographic
information. GML is a profile (encoding) of XML.\
Compiled from multiple sources including:\
[http://support.esri.com/index.cfm?fa=knowledgebase.gisDictionary.search&search=true&searchTerm=gml![](media/image1.png){width="7.291666666666667e-2in"
height="7.291666666666667e-2in"}](http://support.esri.com/index.cfm?fa=knowledgebase.gisDictionary.search&search=true&searchTerm=gml)

**Georeferencing**\
To establish a relationship between page co-ordinates on a planar map
and known real-world co-ordinates. Georeferencing allows geographic data
sets to be analyzed and compared with one another.\
Compiled from multiple sources including:\
Retrieved July 31, 2006 from,
[http://www.geo.ed.ac.uk/agidexe/term?1228![](media/image1.png){width="7.291666666666667e-2in"
height="7.291666666666667e-2in"}](http://www.geo.ed.ac.uk/agidexe/term?1228)\
Retrieved July 6, 2006,
[http://support.esri.com/index.cfm?fa=knowledgebase.gisDictionary.search&search=true&searchTerm=georeference![](media/image1.png){width="7.291666666666667e-2in"
height="7.291666666666667e-2in"}](http://support.esri.com/index.cfm?fa=knowledgebase.gisDictionary.search&search=true&searchTerm=georeference)

**Geospatial**\
Relating to physical features of the earth and their geographic
location, including both natural and man-made features. Geospatial data
refers to information derived from maps or remote sensing techniques,
such as aerial photography or satellite imagery.\
Compiled from multiple sources including:\
Webster\'s New Millennium Dictionary of English, Preview Edition (v
0.9.6)\
Copyright © 2003-2005 Lexico Publishing Group, LLC\
Retrieved June 8, 2006, from:
[http://dictionary.reference.com/search?q=geospatial&r=66![](media/image1.png){width="7.291666666666667e-2in"
height="7.291666666666667e-2in"}](http://dictionary.reference.com/search?q=geospatial&r=66)\
Directions Magazine: the worldwide source for Geospatial Technology\
Retrieved July 26, 2006, from:
[http://www.directionsmag.com/press.releases/index.php?duty=Show&id=10412&trv=1![](media/image1.png){width="7.291666666666667e-2in"
height="7.291666666666667e-2in"}](http://www.directionsmag.com/press.releases/index.php?duty=Show&id=10412&trv=1)

**Raster**\
An image formed using individual dots with color values, called cells
(or pixels). Cells are viewed in a rectangular grid with each cell
evenly spaced. Aerial photographs and satellite images are examples of
raster images used in mapping.\
Raster layers in a GIS system can depict such information as elevation,
precipitation, and temperature.\
Compiled from multiple sources including:\
Retrieved July 28, 2006 from
[http://data.geocomm.com/helpdesk/glossary-r.html![](media/image1.png){width="7.291666666666667e-2in"
height="7.291666666666667e-2in"}](http://data.geocomm.com/helpdesk/glossary-r.html)

**Remote Sensing**\
RS is the process of using a recording device not in physical contact
with the surface being analyzed to obtain data.\
Methods include aerial photography and using sensors sensitive to
various bands of the electromagnetic spectrum. Equipment can be deployed
from aircraft, satellite or space probe.\
Compiled from multiple sources including:\
Retrieved July 28, 2006 from
[http://data.geocomm.com/helpdesk/glossary-r.html![](media/image1.png){width="7.291666666666667e-2in"
height="7.291666666666667e-2in"}](http://data.geocomm.com/helpdesk/glossary-r.html)

**Shapefile**\
Shapefile is the name of the proprietary digital vector storage format
created by ESRI Corporation. Shapefiles are used and created in software
such as ArcView, Arc/Info, ArcGIS and other widely used GIS software.\
A shapefile consists of multiple files that together generate a data
layer in a Geographic Information System (GIS). There are three required
files that are stored and deployed together in a shapefile:\
.shp - the file that stores the feature geometry.\
.shx - the file that stores the index of the feature geometry.\
.dbf - the dBASE file that stores the attribute information of
features.\
Other files can be added to the shapefile to carry additional
information such as projection and metadata.\
Compiled from multiple sources including:\
Retrieved June 29, 2006 from,
[http://en.wikipedia.org/wiki/ESRI_shapefiles![](media/image1.png){width="7.291666666666667e-2in"
height="7.291666666666667e-2in"}](http://en.wikipedia.org/wiki/ESRI_shapefiles)\
Retrieved June 29, 2006 from,
[http://walrus.wr.usgs.gov/infobank/programs/html/definition/shapefile.html![](media/image1.png){width="7.291666666666667e-2in"
height="7.291666666666667e-2in"}](http://walrus.wr.usgs.gov/infobank/programs/html/definition/shapefile.html)\
Retrieved July 26, 2006, from,
[http://support.esri.com/index.cfm?fa=knowledgebase.gisDictionary.search&search=true&searchTerm=shapefile![](media/image1.png){width="7.291666666666667e-2in"
height="7.291666666666667e-2in"}](http://support.esri.com/index.cfm?fa=knowledgebase.gisDictionary.search&search=true&searchTerm=shapefile)

**Vector**\
Vector data (used in a GIS system) is one method used to store spatial
data. Features are defined by their boundaries only and curved lines are
represented as a series of connecting arcs. Vector data is expressed as
X,Y,Z coordinates. Examples of vector layers include schools (points),
street networks (lines), and voting districts (polygons).\
Compiled from multiple sources including:\
Retrieved June 9, 2006,
[http://www.geo.ed.ac.uk/agidexe/term?349![](media/image1.png){width="7.291666666666667e-2in"
height="7.291666666666667e-2in"}](http://www.geo.ed.ac.uk/agidexe/term?349)\
Retrieved July 31, 2006,
[http://data.geocomm.com/helpdesk/glossary-v.html![](media/image1.png){width="7.291666666666667e-2in"
height="7.291666666666667e-2in"}](http://data.geocomm.com/helpdesk/glossary-v.html)

**XML**\
XML is an acronym for Extensible Markup Language. Developed by the World
Wide Web Consortium (W3C), it is a standardized markup language for
designing text formats. It enables the interchange of data between
computer applications. XML is a set of rules for creating standard
information formats using customized tags and sharing both the format
and the data across applications.\
Compiled from multiple sources including\
[http://support.esri.com/index.cfm?fa=knowledgebase.gisDictionary.search&search=true&searchTerm=xml![](media/image1.png){width="7.291666666666667e-2in"
height="7.291666666666667e-2in"}](http://support.esri.com/index.cfm?fa=knowledgebase.gisDictionary.search&search=true&searchTerm=xml)
GIS Dictionaries and Glossaries:\
[http://www.agi.org.uk/bfora/systems/xmlviewer/default.asp?arg=DS_AGI_TRAINART_67/\_firsttitle.xsl/87![](media/image1.png){width="7.291666666666667e-2in"
height="7.291666666666667e-2in"}](http://www.agi.org.uk/bfora/systems/xmlviewer/default.asp?arg=DS_AGI_TRAINART_67/_firsttitle.xsl/87)<http://www.fgdc.gov/metadata/csdgm/glossary.html>![](media/image1.png){width="7.291666666666667e-2in"
height="7.291666666666667e-2in"}<http://www.gis.com/whatisgis/glossaries.html>![](media/image1.png){width="7.291666666666667e-2in"
height="7.291666666666667e-2in"}<http://www.landinfo.com/resources_dictionaryAD.htm>![](media/image1.png){width="7.291666666666667e-2in"
height="7.291666666666667e-2in"}

**Appendix 3:**

**Collection Levels**

0 - Out of Scope\
1 - Minimal Level\
2 - Basic Level\
3 - Study Level\
4 - Research Level\
5 - Comprehensive Level

**Appendix 4: For more information (links and bibliography)**

-   The Center for International Earth Science Information Network
    (CIESEN)\
    [http://www.ciesin.org/![](media/image1.png){width="7.291666666666667e-2in"
    height="7.291666666666667e-2in"}](http://www.ciesin.org/)

```{=html}
<!-- -->
```
-   Digital Curation Centre, United Kingdom\
    [http://www.dcc.ac.uk/![](media/image1.png){width="7.291666666666667e-2in"
    height="7.291666666666667e-2in"}](http://www.dcc.ac.uk/)

```{=html}
<!-- -->
```
-   Federal Geographic Data Committee (FGDC)\
    [http://www.fgdc.gov/![](media/image1.png){width="7.291666666666667e-2in"
    height="7.291666666666667e-2in"}](http://www.fgdc.gov/)

-   FGDC Content Standard\
    [http://www.fgdc.gov/standards/projects/FGDC-standards-projects/metadata/base-metadata/index_html![](media/image1.png){width="7.291666666666667e-2in"
    height="7.291666666666667e-2in"}](http://www.fgdc.gov/standards/projects/FGDC-standards-projects/metadata/base-metadata/index_html)

```{=html}
<!-- -->
```
-   National Archives and Records Administration (NARA)\
    Requirements for transfer of permanent electronic records,
    geospatial data:
    [http://www.archives.gov/records-mgmt/initiatives/digital-geospatial-data-records.html![](media/image1.png){width="7.291666666666667e-2in"
    height="7.291666666666667e-2in"}](http://www.archives.gov/records-mgmt/initiatives/digital-geospatial-data-records.html)

```{=html}
<!-- -->
```
-   National Digital Information Infrastructure and Preservation Program
    (NDIIPP)\
    [http://www.digitalpreservation.gov/![](media/image1.png){width="7.291666666666667e-2in"
    height="7.291666666666667e-2in"}](http://www.digitalpreservation.gov/)

```{=html}
<!-- -->
```
-   National Geospatial Digital Archive (NGDA)\
    [http://www.ngda.org![](media/image1.png){width="7.291666666666667e-2in"
    height="7.291666666666667e-2in"}](http://www.ngda.org/)

```{=html}
<!-- -->
```
-   National Library of Australia, Preserving Access to Digital
    Information (PADI)\
    [http://www.nla.gov.au/padi/index.html![](media/image1.png){width="7.291666666666667e-2in"
    height="7.291666666666667e-2in"}](http://www.nla.gov.au/padi/index.html)

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-   North Carolina Geospatial Data Archiving Project (NDGDAP)\
    [http://www.lib.ncsu.edu/ncgdap/![](media/image1.png){width="7.291666666666667e-2in"
    height="7.291666666666667e-2in"}](http://www.lib.ncsu.edu/ncgdap/)

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-   Maine GeoArchives: A collaborative project between the Maine State
    Archives and the Geolibrary Board\
    [http://www.maine.gov/sos/arc/GeoArchives/geoarch.html![](media/image1.png){width="7.152777777777777e-2in"
    height="7.152777777777777e-2in"}](http://www.maine.gov/sos/arc/GeoArchives/geoarch.html)

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-   United States National Satellite Land Remote Sensing Data Archive\
    [http://edc.usgs.gov/archive/nslrsda/![](media/image1.png){width="7.152777777777777e-2in"
    height="7.152777777777777e-2in"}](http://edc.usgs.gov/archive/nslrsda/)