# Presentation: 635015

## Making the Most of Biological Water Quality Monitoring:

- Ecological and Toxicological Water Quality Data Elements
- ACWI Meeting
- Herndon, VA
- September 15, 2004

**Notes:**
Introduce self, colleagues (Jerry, Herb, Charlie)
All members of the Nat’l Water Quality Monitoring Council’s Methods & Data Comparability Board
Today: introducing the WQDE’s as tools for producing, & maintaining, and using water quality monitoring data of known quality
Theme: Ensuring Data & Information Comparability

## Understanding the interactions between humans & the environment requires data of known quality collected at different spatial & temporal scales from many scientific disciplines. 

- Because no single group can collect all the data needed to understand and deal with the complexities of natural systems, we must learn to _share data effectively_.

***“******Good data documentation for effective data sharing”***

**Notes:**
There’s been considerable enthusiasm for bringing together scientific information from diverse sources. 
Data generators (aka data producers) need to collect good-quality data, to make datasets available, and most importantly, to document the data so that they can be understood & evaluated
Data documentation allows data users (aka data consumers) to gain a uniform understanding of the content and suitability of datasets for their intended purpose(s).

## Benefits of Data Sharing

- Increased pool of reference sites available to any one program
- Enhanced ability to make scientifically defensible judgements on water quality
- Provides decision makers with better information with which to devise and implement monitoring strategies
- Increased ability to use data produced by other programs & encourages collaborative efforts
- Reduced costs

**Benefits of Data Sharing**

**Notes:**
There are numerous advantages to data sharing:
to examine water quality monitoring questions at broader spatial, temporal, & taxonomic scales
increased sample size, especially reference n --> increased precision!
How is “impaired” defined? Is the waterbody unimpaired or impaired? What is the source of the impairment? How many impaired waters are there? What needs to be done to bring impaired waters up to standard? Data sharing & information exchange leads to improved consistency. 
from helping managers efficiently design and implement more effective programs, to reducing the number of sites requiring sampling
fosters creativity & the transfer of information & innovations. 
by sharing information, more effective use can be made of limited resources
HOWEVER, there are a number of obstacles to effective data sharing...

## Barriers to Data Sharing

- DATA EXCHANGE
- DATA MGT
- DATA ACCESS
- DATA INTERPRETATION
- DATA DOCUMENTATION
- it all comes back to _metadata_

**Barriers to Data Sharing**

**Notes:**
Sources of variability in datasets which limit use. Integrating data from widely different sources of mixed methods & unknown quality has historically been a problem for scientific investigations.
administrative & technical hindrances: fed-fed, fed-state, state-state, volunteer-state/fed/vol, historic-current
keeping data organized & maintained to facilitate data exchanges. Good data management is vital for effective data sharing. Tends to be a disconnect between data collection and data management...important to think about how data will be managed before collecting new data. 
often reside on paper or in computer files, not in centralized systems. And information obtained from data warehouses is of questionable reliability. Information in databases is only as good as the information submitted. IOW, a database can be used to integrate data that are too different to be integrated by any other means.
can’t make statistically valid inferences about status/trends. 
it all comes back to METADATA... descriptive information about the data.

## A Few Good Quotes

- FGDC (2000) : "Data producers and users cannot afford to be without documented data.”
- NAS (2002):“Far too many environmental research projects give insufficient attention, in either the planning or the implementation stage, to the long-term archiving of their data sets.”
- GAO (2002):  “EPA should provide clear guidance to states on the information they should use to describe their methods for identifying impaired waters”
- GAO (2004): “[recommend] development of clear guidance on metadata standards so that data users can integrate data from various sources”

**Notes:**
Many scientists resist writing metadata...”too expensive” “too onerous” “too boring”
Often costs of data curation & maintenance not factored into a program’s budget
Data producers and users cannot afford to be without documented data.

## What are Water Quality Data Elements

- <date/time>

**What are Water Quality Data Elements**

- Information about data that answer basic questions to facilitate data exchange:
- Who?    (Which organizations are responsible?)
- What?   (What was monitored and found?)
- Why?    (Why was the monitoring conducted?)
- When?  (When was the monitoring done?)
- Where? (Where was the monitoring done?)
- How?    (How was the sampling/testing done?)

## Data Element Modules

- <date/time>

**Data Element Modules**
- 1 - Contacts
- 2 - Analyte / Endpoint Result
- 3 - Reason for Sampling
- 4 - Date/Time of Sampling
- 5 - Location
- 6 - Sample Collection Methods
- 7 - Sample Analysis Methods & QA/QC

**Notes:**
The data elements were developed using a modular strategy
Each module represents a category of metadata information
Efficient organizational framework for integrating different analytes 
Allows for changes to be easily made or for organizations to customize the data elements to their monitoring needs

## Status of Data Elements

- <date/time>

**Status of Data Elements**

- Chemical and microbiological elements approved by ACWI on May 15, 2001 and being implemented / considered by several agencies
- Population/community elements approved by the Methods Board (2003) and Council (2004)
- Toxicity elements approved by the Methods Board (2003) and Council (2004)
- Habitat elements drafted – in progress
- Plan to address biomarkers and sediment data elements soon

## Biology Data Elements Workgroup Charge

- <date/time>

**Biology Data Elements Workgroup Charge**

- To prepare a set of data elements to be used to structure the sharing and archiving of biological data.
- The list of data and metadata elements is intended to *promote data sharing* *but* *without being an exhaustive list of every possible data element that could be reported.*

## Overlap in Elements (Depending on Type of Data Reported)

- <date/time>

**Overlap in Elements ****(Depending on Type of Data Reported)**

- Toxicity sample collection -  chem/micro sampling elements
- Plankton/algal surveys – chem/micro sample processing elements
- Organism tissue chemical analysis - Chemical analysis elements
- Organism tissue sampling – population / community sample prep elements

**Notes:**
So the DE lists are linked by modular elements in common as well as by overlap
Therefore these new lists shouldn’t be viewed as add-ons, but as additional categories of information relevant to particular aspects of water quality monitoring for organizing & integrating the flow of information generated by a water quality monitoring program

## Biological Data Elements Modules Under Consideration

- “Biological” = ecological and toxicological
- Biological assessment (bioassessment) evaluates conditions of waterbody using biosurveys & other direct measurements of resident biota
- Toxicology (ecotoxicology) studies the harmful effects of chemicals on biota in the context of the natural environment:
- biomonitoring: evaluation of effects using ecological indicators, populations, etc.
- bioassays: evaluation of real toxicity under controlled conditions in the lab

## Points to Ponder

- A WQDE guidance document is currently under review
- Minimum elements needed to facilitate data exchange & evaluate methods & data comparability
- Categories of information relevant to various aspects of wq monitoring practices
- Most organizations already collect this info; it’s just a matter of documenting it
- New technologies make implementation less onerous

**Notes:**
DEs not not sets of required information...
Interconnections between other modules
The information needed to create metadata is readily available before the data are collected.

## Proposed Timeline for Approval

- 10/1/04:  Guidance document on WQDE’s to NWQMC
- 10/22/04:  Guidance document on WQDE’s to ACWI
- 11/19/04:  ACWI comments on bio data elements and guidance document
- distribute lists within organizations & solicit feedback
- 12/17/04: Final Action
- ACWI conference call to discuss data elements and guidance document
- vote via email
- letter of support/formal adoption

**Notes:**
We are asking you to review & ultimately approve these lists
NJ Water Monitoring Council & other groups are asking that ACWI approve the bio elements soon

## "If you think the cost of metadata production is too high - you haven't compiled the costs of NOT creating metadata: loss of information with staff changes, data redundancy, data conflicts, liability, misapplications, and decisions based upon poorly documented data." 

*FGDC (2000)*

**Notes:**
Too many scientists think of metadata as something you do at the end of the study. Ideally, metadata should be a key component in every phase of the data development process,starting with the initial planning. 
a common characteristic of programs that don’t meet expectations for producing information with “known confidence” is that the Objectives for monitoring are not clearly, precisely stated and understood. 
and the objectives determine the monitoring design.