xe/EPA
United States
Environmental Protection
Agency
Office of Water
(WH-556F)
EPA 503/9-91/008
July 1991
National Estuary Program
?!EADQUAHTERS LIB
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TABLE OF CONTENTS
PRACTICAL TOOLS AND TECHNIQUES
I. Workshop Objectives 1
n. Opening Roundtable Discussion: NEP Data Management
Concerns, Goals and Objectives 1
ffl. Successful Data Management Solutions From Tier I and
Tier II Representatives: Goals and Objectives 7
A. Collection of Historical Monitoring Data 7
B. Collection of New Monitoring Data 9
C. Analysis of Data for Characterization , 13
D. Data Management Systems Design 17
IV. Small Group Discussion of Data Management Issues 20
A. Data Collection Methodologies 20
B. QA/QCofData .23
C. Hardware/Software Alternatives 24
D. Tools for Analyzing Monitoring Data 25
V. National Data Management System Resources 27
A. ODES/STORET Bridge 27
B. NEP Inventory 29
C. NOAA Systems (COMPAS) 31
D. ODES/GIS Connection 33
PLANNING AND PUTTING IT ALL TOGETHER
I. NEP Data Management Policy: Review 36
A. Need for an NEP Data Management Policy 36
B. Issues Resulting from the Policy 36
C NEP Support 37
D. EPA Data Management System Modernization 38
Workshop Summary
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II. Costs and Benefits of Data Systems Development ....40
A. ODRM System Life Cycle Development Methodology &
EPA Approved Hard ware/Software 40
B. Long-term Systems Maintenance and Operations - Issues 42
HI. Proposed Action Items 45
Appendix A: Small Discussion Groups A-l
Appendix B: Workshop Participants B-l
Appendix C: Summary of Participants' Comments C-l
Workshop Summary
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PRACTICAL TOOLS AND TECHNIQUES
I. Workshop Objectives
Mark Curran, Chief of the Estuarine Management Branch of the Oceans and
Coastal Protection Division (OCPD), welcomed the participants and thanked
them for attending the Workshop. He explained that the Office of Water has
been reorganized and that OCPD maintains the responsibility for overseeing
the National Estuary Program (NEP).
Mr. Curran explained that the issues associated with data management for the
NEP have been neglected in the past. He added that there has been a long-
standing need for a Workshop to get the "people in the trenches" of data
management together to discuss common issues, goals and problems.
The importance of data management when developing a CCMP was stressed
by Mr. Curran. He noted that the ability to manage data is key in providing
understandable information, and that the data provides the ability to measure
the effectiveness of management plans.
Two objectives for the Data Management Workshop were highlighted by Mr.
Curran:
1) To gather together the data management experts from the estuary
programs to learn from each others experiences.
2) To identify the types of data management support needed by the
programs.
Mr. Curran commented that the agenda should accomplish these objectives,
but that all of the issues could not possibly be covered during the two day
Workshop. However, the contacts the participants made at the Workshop
should serve as a source of information to resolve future issues.
II. Opening Roundtable Discussion: NEP Data Management
Concerns, Goals and Objectives
Joel Salter, the data management coordinator for the NEP, led the opening
round table discussion which was designed to give a spokesperson from each
program the opportunity to describe the program's data management
concerns, goals and objectives. Fourteen out of seventeen programs were
represented.
Workshop Summary
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A. Individual Estuary Program Comments
Albemarle-Pamlico Estuarine Study (Tier I): Tim Johnson stated that the
main goal of the APES program is to build an integrated data base that can
perform statistical and spatial analyses. APES has spent a considerable
amount of effort developing a Geographic Information System (GIS) for
spatial data analysis. APES is attempting to reach out to other programs and
organizations to gather data and to obtain support for continuing the data
management effort after the program ends. An additional data management
goal is to develop communication links to other systems including the IBM
9000 computer at the National Computer Center (NCC) in North Carolina.
Mr. Johnson also identified several program concerns regarding data
management. These concerns include obtaining the resources that will be
necessary to maintain the data base, pulling data together from different
sources so that it is compatible, making the data base accessible to the public,
and developing a method for handling temporal data in a GIS.
Barataria-Terrebonne (Tier in); Greg DuCote stated that the program's main
goals are to collect as much data as possible, to make the data accessible to
researchers and the public, and to be able to successfully manage the data for
meaningful analyses. Barataria-Terrebonne has a grant from the Department
of Energy to collect spatial data layers which will assist in the program's data
management effort. Several concerns were also noted by Mr. DuCote
including the problems associated with providing data accessibility for a
variety of users. In addition, the program is concerned with coordinating all
of the data that is collected, so that it is in a compatible format.
Buzzards Bay Project (Tier I): Neil MacGaffey identified several goals for the
project. Specifically, the project is striving to develop additional spatial data
layers including sub-basin drainage areas and shellfish beds, to compile a
descriptive index of data so that available data can be identified, to provide
on-line access to users, and to provide data management support for project
activities.
Mr. MacGaffey also discussed several concerns which stem from the need to
prioritize data management objectives within the program. A clear
description of data management expectations needs to be established.
Establishing expectations early in the program assists data managers in
prioritizing objectives and tasks.
Casco Bay (Tier ffl): Christopher Kroot relayed to the group that the Casco Bay
program sees data management as an essential part of developing a CCMP.
As a result, the program started planning for its data management system
immediately. Mr. Kroot indicated that the program is in the process of
identifying what management decisions need to be made, so that the
Workshop Summary
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necessary data can be collected and coordinated into a useful, compatible, and
accessible format. Currently, the data management system developed by
Casco Bay addresses at least half of the program's objectives.
In order to make the data accessible, Mr. Kroot explained that the program has
chosen to use the ODES/GIS Connection developed by EPA. Rather than
develop a new system, the program is relying on the existing ODES system for
data storage and maintenance. The program is designing a specialized user-
interface for the ODES/GIS Connection to specifically address program needs.
Delaware Estuary Project (Tier n): Mindy Lemoine stated that currently no
one is specifically assigned to focus on data management for the project. The
project plans to use existing data management systems for their data storage
and analysis needs including ODES, COMPAS, and other NOAA systems. Ms.
Lemoine indicated that difficulties arise from conflicting objectives between
the three states that are involved in the project (i.e., NJ, DE, and PA). For
example, New Jersey has developed a GIS, but Delaware has not. As a result,
the project will not develop its own GIS, but will coordinate the data available
from the three states and utilize the GIS resources already available. She
indicated that the project does not have the financial resources to develop its
own GIS.
Galveston Bay National Estuary Program (Tier II): Robert McFarlane stated
that the Galveston Bay program is not developing a data management
system. He indicated that the main goal for the program has been to develop
a data inventory which provides an electronic literature search including a
bibliography. This data inventory allows a user to query the system to
identify where the data can be located or if it is still available. The Galveston
Bay Information Center, located at Texas A&M University, maintains all
available literature and reports. One of the program's largest problems has
been lost due to a lack of maintenance (e.g., data on magnetic tapes, etc.)
Archiving data has not been a state priority. As a result, 80% of the data
collected for Galveston Bay has been lost.
Mr. McFarlane explained that the program has been supporting the use of
COMPAS, which has been adopted by many of the state agencies in Texas.
The system will be fully functional within the year. The program has also
incorporated the Texas National Resources Information System (TNRIS) into
its data management strategy. TNRIS coordinates all state and federal data
and provides public access to the data.
Galveston Bay is not meeting the dates established in its data management
schedule for developing its CCMP, according to Mr. McFarlane. As a result,
the program is forced to begin developing its CCMP without any data analysis.
Mr. McFarlane explained that the program is going to rely on expert opinion,
since there is not enough data to perform the necessary analyses.
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Indian River Lagoon (Tier III): Bob Day stated that the program is only in the
beginning stages of developing its data management plan. The program's
main goals include providing accessibility to data for a wide range of users
through Florida's environmental learning centers. The environmental
learning centers are used by scientists as well as elementary school children,
so the program is faced with providing information to a wide audience. The
program has stored all of its water quality monitoring data in STORET and is
planning on using the ODES/STORET Bridge to access their data. The water
management districts have spatial data layers that cover the lagoon, and these
data layers will be available to the program.
Long Island Sound Study (Tier I); Cynthia Pring-Ham explained that the
program is continuing to develop its data management strategy. The
program has been extended a year, because it is behind in developing its
CCMP. She indicated that data management issues do not receive the
attention that they need to help address program objectives. In the short-
term, Ms. Pring-Ham indicated that the program is developing an index of
data which contains three years worth of data.
Ms. Pring-Ham identified several goals for the program which include
developing models to determine the monitoring needs of the program,
designing a data management system to satisfy the identified monitoring
needs, and insuring that the data management system has adequate analytical
capabilities.
Two concerns were identified by Ms. Pring-Ham. First, the program is
attempting to combine data collected by two different states, New York and
New Jersey. Second, the program recognizes that it will take considerable
time and money to review the historical data for Long Island Sound to see if
there is sufficient QA/QC information to make the data useful. In addition,
she indicated that the historical data is in inconsistent formats. As a result, it
must be converted to a standard format in order for the data to be accessible.
Massachusetts Bays Program (Tier ffl): Dillon Scott explained that data
management is one of the Massachusetts Bays Program's top priorities. As a
result, the program is establishing specific objectives for data management.
Ms. Scott indicated that there is only one person responsible for data
management, so it is often difficult to determine how to adequately address
the variety of data management issues.
The program's data management system is linked to a state system which
maintains ARC/Info data layers. The program is developing an index of
research data collected for the Bay and focusing on making the data
compatible with the states GIS. The GIS will provide access to the data for a
variety of users including the public.
Workshop Summary
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Narragansett Bay Project (Tier I): Stephen Hale explained that the
Narragansett Bay project began a massive data collection effort within the first
year of the program. He indicated that the program has set specific goals for
characterization. Specifically, the project is striving to collect and verify
historical monitoring data, to modify the data management system to be able
to sustain long-term monitoring, and to develop a database for managing
long-term trends.
Mr. Hale explained that the program has been successful in its data
management effort. He attributes this success to the development of one
central data management system and a computerized bibliography. In
addition, the program obtained support and money to further its data
management objectives.
Although the data management effort for the program has been successful,
Mr. Hale identified some concerns. First, the program is trying to consolidate
all of its monitoring program objectives, so that the data management system
may address as many as possible. Second, the program is beginning to face the
problem of obtaining funding for the data management system after the
program ends.
Santa Monica Bay Restoration Project (Tier n): Robert Smith explained that
the program currently has large monitoring programs that are managed by
independent sources. One of the program's goals is to move toward data
collection by regional programs instead of independent sources. However,
Mr. Smith indicated that standardizing all of the data that has been collected
in different formats from the independent sources will be a challenge.
The program is planning to use a dispersed data management system. The
option to develop a centralized system was eliminated because the program
feels that this will result in data duplication. In addition, a dispersed system
will allow updates to data to be done quickly and will allow immediate access
to the data. Mr. Smith also indicated that the program is developing an index
of the data in an effort to keep track of where the available data is located.
Sarasota Bay National Estuary Program (Tier II): Dave Tomasko indicated
that a workshop for all of the Pis collecting data for Sarasota Bay will be held
in June. The program has developed a standardized format for collecting data
which is based on ODES codes. The workshop is designed to discuss the
standard format with the Pis and resolve any questions or concerns.
In the long-term, Mr. Tomasko indicated that the program will be moving
from the characterization phase of the program to monitoring. In an effort to
effectively use the program's financial resources, the number of stations
sampled will be reduced, so that monitoring can be concentrated in
representative areas.
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The data being collected for six out of the eleven studies funded by the NEP
will have spatial information. However, the program is not planning to
develop a GIS, and will send the data elsewhere for digitization. Mr.
Tomasko explained that the program will work with the GIS system
developed by the South West Florida Water Management District, but the
program currently has not had a strong demand for spatial data.
Tampa Bay (Tier HI): Holly Greening explained that the program has not yet
developed its data management strategy. The program is faced with
coordinating and standardizing the monitoring program data from eleven
governmental agencies. A workshop is planned for this summer to facilitate
this effort.
Ms. Greening indicated that the program is placing an emphasis on GIS to
analyze spatial data. In addition, the water quality data for the system is
maintained in STORET, and the biological data will be submitted to ODES.
Thus, the program is interested in using the ODES/STORET Bridge to access
all of the data.
B. Common Themes Identified Throughout the Estuary
Programs
Several common themes were identified throughout many of the comments
made by the estuary spokespeople. These themes are listed below and are
discussed in more detail in the sections that follow.
Data integration issues
Communication between systems
Data accessibility for principle investigators & the public
Available tools to use the data
Identification of the intended use of the data
Importance of spatial data and GIS applications
Data Indexes to identify available data
Establishment of priorities and expectations for data management
Develop better data coordination between states
Identification of perishable data
Importance of sound data analysis during characterization, CCMP
development and implementation, and long-term monitoring
High cost for determining the usefulness of historical data
Need to use standardized data collection formats
Importance of identifying sources of funding for data management
Workshop Summary
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IE. Successful Data Management Solutions From Tier I and Tier II
Representatives: Goals and Objectives
A panel of Tier I and II data managers, moderated by Bob King, addressed
successful data management solutions. Neil MacGaffey discussed the
collection of historical monitoring data. Stephen Hale presented issues
concerning the collection of new monitoring data. A discussion on the
analysis of data for characterization was presented by Tim Johnson. Tom
Gulbransen discussed data management systems design. A question and
answer period followed the four presentations. The comments made during
the question and answer period are incorporated into the pertinent sections.
A. Collection of Historical Monitoring Data
Neil MacGaffey - Buzzards Bay Project
The use of historical data is strongly affected by changes in data
methodologies and available technology. For example, the use of personal
computers and commercial data management software has increased due to
the reduction in cost. The availability of hardware and software in return has
led to a standardization effort to use the same data management tools and
data formats. This standardization effort has led to some integration among
data management systems. These changes affect the user's expectations of
how easily the historical data can be manipulated. As a result, those
responsible for the original data collection effort cannot always be faulted for
the complexities associated with historical data, because the methods used to
manage and collect the data have advanced since the data was collected. The
following four major issues were addressed:
1. Documentation
Quality control documentation usually does not accompany the data and
often is not included in the data set report. For example, information on
limits of detection is often missing. As a result the limits must be assumed
based on the analytical technique used to collect the data. In addition, data
collection references are usually incomplete or missing. Often the agency that
collected the data no longer exists. In other cases, the agency no longer has
the data report or cannot find it. Additional documentation problems result
from missing or incomplete data dictionaries. Without the supporting data
element descriptions, it is difficult to identify the information maintained in
each field.
2. Variations in Temporal and Spatial Coverage
Historical data sets were usually collected for purposes unrelated to current
program needs. As a result, the spatial and temporal coverages are often
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inadequate for current analyses. However, exceptions do exist. For example,
in the one instance in Buzzards Bay where long term data collection has
existed, some limited trend analysis is possible even though the data were
originally collected for unrelated purposes.
3.
File Formats and Standardization
Each file usually has a unique format. As a result, each data set poses separate
data transfer problems. These problems allow little opportunity for
developing efficiencies in the data transfer process. An inordinate amount of
time can be spent diagnosing and solving intricate file and field format
problems and inconsistencies. The problems associated with massaging data
into standard formats exists regardless of the system or application being used.
In an effort to facilitate the data standardization process, the Buzzards Bay
Project hired an outside contractor to keypunch some data sets, standardize
the file formats of digital data, collect quality assurance information, and add
important information such as latitude/longitude coordinates for station
locations. Locating, obtaining, "scrubbing", and standardizing the format of
existing data sets is a task requiring day-to-day attention to details; it is
extremely difficult to track these details reliably when other tasks provide
distractions. Having a contractor focus exclusively on the task resulted in
more consistent data in a standard format. The standard format, the data
scrubbing, and some quality assurance performed by the contractor, made
moving data into the Project's ORACLE database easier to accomplish.
4. Missing Information
Often essential information is missing or available only after considerable
collection effort by data management staff. This information must be
assembled to determine the potential usefulness of the data set. Missing
information may include: sample values (e.g., concentrations),
units of measurement, methods for some or all of the parameters being
measured, station depths, coordinates for station locations, environmental
data (i.e., wind direction, rain, or tide). In addition, the definitions for coded
fields are often missing. As a result the codes used in the data set are
meaningless to the investigators. If standardized codes were used, such as
NODC codes or CAS numbers this problem is reduced.
Workshop Summary
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B. Collection of New Monitoring Data
Stephen Hale - Narragansett Bay Project
Four major topics concerning the collection of new monitoring data were
addressed. These topics include the goals of a long-term monitoring data
management effort, general issues related to collection of new monitoring
data, information needed by data management personnel in order to
effectively collect new monitoring data, and actions that should be taken by
data management personnel prior to the start of data collection.
1. Goals of a long-term monitoring data management effort
The recommendations developed from the characterization process that are
incorporated in the CCMP are tested through a long-term monitoring data
management effort. The long-term monitoring data management effort
provides a long-term, consistent data base that can be used by managers and
scientists to discover and explain trends in the estuary's ecosystem. The long-
term monitoring of the estuary should indicate if the recommendations
implemented in the estuary's CCMP are having the desired effect.
The ultimate goal of the program's data management system is to provide
access to quality data so that the data can be assimilated into useful
information to provide the support for management decisions. Achieving
this goal provides the estuary program managers with accessibility to quality
information, so they can do a better job of managing the estuary and its
watershed. Although estuary program management decisions are influenced
by a variety of factors, it is the responsibility of the program's data managers
to provide a platform for decision making based on data and scientific
information.
An additional goal in the development of the data management system is to
make the monitoring data available and easily understandable for a broad
range of managers, researchers, and the public. Although these goals are
difficult to attain, data managers should strive to achieve the highest quality
of data and greatest accessibility when developing the system.
Many states are discovering that providing accessibility to the monitoring
data at a local level will ensure additional funding for monitoring programs.
It is especially important to provide access for the local levels, because local
governments, public works departments, and the water districts are the
people who are actually making the decisions that affect the environment.
Moreover, states are much more inclined to provide funding for monitoring
programs that generate data that is accessible to state and local level programs.
Workshop Summary
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The underlying idea behind the estuary program is to build up the state
agencies to the point where they can assume the responsibility for the
program's data management and analysis. Thus, it is very important to
involve the state agencies in developing a monitoring plan for the estuary.
2. General issues related to collection of new monitoring data
When planning the data management effort for the program, the program
managers must determine if the system will track only monitoring data, or if
it will function as a true central data repository for the estuary, Narragansett
Bay has developed a central storage center for monitoring data as well as
other types of data, including NOAA bathymetry data and USGS water quality
information. The program selected this approach because analysts need access
to many types of data other than monitoring data. In addition, different
analysts need access to the same data. If a central data storage location is not
used, two different analysts may store and maintain the same data in their
individual systems which results in a duplication of effort. By maintaining
all types of data in a central location, users have access to a variety of data and
the problems associated with duplication are eliminated.
The problem with developing a multi-disciplinary central data base for an
estuary is that no agency or program has the responsibility or mandate for
developing and maintaining it. Although federal, state and local agencies
and universities heartily support the idea, none of these organizations are
mandated to provide it. As a result, uncertainty remains among many of the
estuary programs regarding how a long-term monitoring data management
effort can be funded. Obtaining a firm commitment from the state in support
of long-term monitoring plays a key factor in planning the program's data
management strategy.
One of the key issues in the long-term monitoring program is that many
different agencies, contractors and citizens monitoring groups are collecting
data. The data managers for the estuary program are trying to pull all of the
information collected together to address the key concerns that the estuary
program has identified. Assimilating all of the data is a time consuming task,
because, the data and quality assurance information are in different formats
and must be standardized. Some of the standardization effort can be
eliminated by specifying that contractors collect and document the data in a
standard format. Since the data is being collected from citizens monitoring
groups on a voluntary basis, the data managers can only stress the importance
of collecting data in a specific format. In addition, the data files from other
agencies will almost certainly need to be massaged into the estuary programs
standardized format, unless the individual agencies can agree on a consistent
format.
Workshop Summary
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3. Information needed by data management personnel in order to
effectively collect new monitoring data
Before a data collection effort is begun, information is needed by the data
management personnel. Specifically, a final list of data file types that will be
collected must be developed. This list should include the specific parameters
and units that will be collected.
The number of stations and frequency of sampling at each station must be
identified for all data file types and parameters. This information will
indicate the amount of data storage space needed to manage the data collected.
The precision, significant digits, detection limit and field collection method
must be identified and stored in the data base for each parameter. In addition,
the data collection, digitization and storage methods must be collected and
maintained in the system. For existing data collection efforts, the data
management personnel must research this information if it is not part of the
data file.
In addition, the data management personnel along with the estuary program
managers and scientists, must determine exactly what will be done with the
long-term monitoring data files once they have been submitted to the central
data system. Specifically, the desired tables, graphs, maps, and statistical
analyses should be identified. This early discussion also provides the
opportunity for the managers and scientists to express their expectations from
the system and allows the data managers to realistically explain whether or
not their expectations are feasible.
4. Actions that should be taken by data management personnel prior to
the start of data collection
Prior to the start of long-term monitoring data collection, the data managers
should provide historical data to the statisticians and monitoring plan
designers so that the most effective sampling design can be developed. The
historical data can provide insight into the most useful sampling parameters,
the number and location of the stations for sampling, and the frequency and
number of samples to be taken at each station.
The data management staff should also modify the data base design to
incorporate any new data types that were not included in the characterization
studies. Please note that this requires the data base structure to provide the
flexibility for changes.
The data management system must also provide a tracking system for
archived samples that records information about each sample taken in the
Workshop Summary
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estuary. The information should include who took the sample, when it was
taken, where it is stored, and what methods were used to collect it.
After the data base design is modified, the supporting documentation (i.e., the
Data Submissions Manual) must be revised to include all data file types in the
final long-term monitoring plan. In addition, all data submissions forms and
formats must be updated. To facilitate the submission of data, the data
management staff should develop procedures with each data collecting
agency to transfer the data and documentation. Wherever possible,
procedures should be implemented to automate the data transfer, checking,
loading, and reporting.
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C. Analysis of Data for Characterization
Tim Johnson - Albemarle-Pamlico Estuarine Study
This discussion defined characterization and presented alternative
approaches for analyzing data during characterization. The use of GIS as a
data analysis tool was discussed using examples from the Albemarle-Pamlico
Estuarine Study. During the open discussion session, several data managers
discussed how their programs have dealt with the complexities of using
historical data in characterization and CCMP development. In addition,
several participants raised questions about the appropriate audience for GIS
applications.
1. What is characterization?
Characterization is the effort to discover the present state of the estuary. The
characterization report should include the status of problems in the estuary
and the sources of the problem. In addition, the report should include trends
identified by the studies initiated to review the problems.
2. Alternative approaches to data analysis for characterization.
Most estuary programs begin the characterization process by using a non-
automated approach where the general state of the estuary is assessed by
experts by reviewing available trend information. Many programs then
move to an automated system where tabulated data may be used to provide
reports and conduct statistical analyses. A third alternative is to incorporate a
geographic information system in a program's data management system, so
that the data may be viewed spatially.
Ideally, the estuary program would have the resources to design a specialized
monitoring program and collect the required data to address the issues related
to the estuary. However, this is not the case, and the estuary programs must
use existing data to characterize the estuary and plan the monitoring
program.
Almost every program is using historical data differently to characterize the
estuary. The differences in the data analysis methods stem from the quantity
and quality of the historical data available and the gaps in data that must be
filled during characterization. All of the programs agree that it is difficult to
adequately factor data management into developing the CCMP within five
years. However, Congress has imposed the five year time limit, and the NEP
developed a program around the time frame. Representatives from several
programs explained how their programs are attempting to factor data
management into the characterization process and into the CCMP
development:
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Casco Bay: The Technical Advisory Committee made it a priority during the
first year to collect a baseline of data. The program took a data inventory of all
state agencies and groups. At the end of the first year, the program will write
a "state of data" report. All of the state agencies, local governments, and
universities are committed to the initial data collection project and have
given their financial support. The program managers understand that a
successful CCMP cannot be developed without incorporating sound data
analyses. The development of the data management system is going to be the
glue that holds all of the agencies and groups together after five years. The
whole purpose of developing the system is to build relationships among the
groups to help them share data.
Delaware Bay: The program is currently developing an inventory of its data,
but the inventory will not be complete until after the period of
characterization. As a result, the program will base its characterization report
on research and expert opinion. The data managers are meeting this summer
to identify gaps in the data, so they can focus on collecting the necessary
information to complete the CCMP.
Albemarle-Pamlico: During the second year of the study, the program
completed a data needs assessment. One of the products of the assessment
turned out, unintentionally, to be a data inventory. The data managers
discovered some purely historical data and identified areas which need to be
expanded. As a result, they have set priorities for the data collection.
3. Use of GIS as a data analysis tool
A GIS is an automated mapping system that allows users to manipulate data
through querying data files and to produce output maps. Data stored in a GIS
has two components, a graphic component and a tabulating component.
These two components are combined by a unique identifying number. Using
GIS provides the advantage of a common frame of reference through spatial
data. Analysts are able to display trends in the estuarine environment and
can visually identify the available data in order to make recommendations
for protecting the estuary. A GIS can be combined with other technologies to
create a total system environment. For example, a GIS can be used in
conjunction with statistical packages to quantify trends.
The ability to communicate the basis for decisions to management and the
public is extremely important to the estuary program. The importance is
magnified by the drastic changes that are going to be proposed, especially in
land use and zoning. The estuary programs are going to have to sell their
decisions to the public who are going to be suffering under the resulting
ordinances that are going to be recommended. Developing a GIS application
provides the tools necessary for displaying the need for radical changes.
Workshop Summary 14
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The disadvantages associated with developing a GIS are due to the cost. Data
development is the most costly aspect of using GIS. It is time-consuming and
requires the use of specialized and expensive hardware and software.
4. Case Study: Albemarle-Pamlico Estuarine Study
The APES study area covers approximately 10 million acres in North Carolina
and 2 million acres in Virginia. The data management team for the program
decided to use a GIS as the data management tool. A GIS allows the program
to integrate as much data as possible into a system that is easily accessible for
researchers as well as the public. The Center for Geographic Information
Analysis, a North Carolina state agency, had a considerable amount of spatial
data already available, that covered the APES study area.
In the initial data needs study, the data management team planned to collect
or develop approximately 65 data layers. However, some of these data layers
were eliminated for one or more reasons such as incompleteness of source
material over a wide geographic area and prohibitive cost of data collection.
At this time, almost 50 data layers are under development. Most of the data
covers North Carolina, because the state is further along in its GIS effort. The
data management team is working with Virginia to ensure that data
development specifications are consistent with those used in the North
Carolina portion of the study area. The information accessible through the
GIS ranges from basic data layers such as hydrography and political
boundaries to specialized layers such as shellfish beds.
The GIS developed for APES runs on a SUN hardware platform, and uses
ARC/Info and ERDAS software. The data management team is stressing the
importance of expanding the communications capability of the GIS to reach
resource managers and the research community. This type of link eliminates
the need for the data to be stored in multiple locations.
The GIS currently is being used to study the inventory of resources in the
Albemarle-Pamlico estuary. Using the GIS, estuary managers can view the
available resources, the location of the resources, and the relationships
among them. The GIS allows managers to target critical areas, especially
wetlands and shellfish disease areas.
The APES program is also using the GIS in water use planning. The
managers are focusing on the competing objectives of conservation,
preservation, and development activities in the coastal areas. The GIS allows
the areas of influence to be viewed spatially with overlays of natural
resources (i.e., shellfish beds) to see if these resources are being negatively
affected by the development going on in the area.
Workshop Summary 15
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5. Audience of GIS Applications
Considerable debate exists among the program data managers regarding the
appropriate audience for a GIS application. For example, it is arguable that it
is unrealistic that a senior manager will turn to a GIS application sitting on
his or her desk to readily access the information necessary to make the
decision. The senior manager is more likely to request the information in a
consolidated form on paper from the senior technical staff. On the other
hand, if a GIS application is menu-driven, the senior manager can have all of
the information immediately. As senior management becomes increasingly
computer literate, they will take advantage of the quick response to the
system. Examples of senior management utilizing GIS applications to made
decisions currently exist. For example, senior managers used a GIS
application to develop Oregon's Clean Water Strategy.
A second argument is that a GIS application should be geared towards senior
technical staff who are more directly involved in the data analyses than the
program managers. In this case, a menu-driven GIS application provides a
set of predictable queries which releases the senior technical staff person from
performing mundane data queries. In addition, the system can also provide
access to the ARC/Info command line, so that the experienced GIS analyst can
address more complicated modeling and analyses. In addition, once the
scientist has made a technical decision, he or she will have the ability to
present the information to senior managers, legislators and the public in a
pictorial form to explain why the decision was made.
Providing a GIS that is accessible and simple to use for the public is a third
alternative. Making the information accessible allows the public to become
involved in the decision making process. As a result, strong public opinion
can influence the program manager's and legislator's decisions regarding
resource allocation for the estuary program.
Workshop Summary
16
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D. Data Management Systems Design
Tom Gulbransen - Battelle Ocean Sciences
NEP data managers face unique challenges which make following the
standard textbook data management systems design process difficult. For
example, the programs must provide accessibility to data for many groups
including the public. In addition, the data managers are faced with the
difficult task of working with many agencies to define the needs of each
group.
1. Factors Influencing a Data Management System Design &
Development
The specific management decisions and analyses that are to be supported by
the system must be written down and prioritized. Each committee should
present its objectives, and the Management Committee should prioritize
them. The master list of prioritized objectives can then be developed into a
data management strategy. From this strategy, an appropriate system design
can emerge.
The agencies involved in the system's development must commit to a time
line and budget. Each task in the system design and development should be
identified, so everyone involved understands the level of effort required.
The tasks can include needs assessment survey costs, requirements
documentation, collecting data, keypunching data, digitizing data, and
maintenance. The financial resource planning incorporated into the data
management system design cannot be based on single-year workplans. The
system will require long-term resources which must be identified from the
beginning of the system's design.
The program coordinator must confirm the commitment of the states to
support the system, because the states will need to take over the responsibility
for the system and long-term monitoring after the five year program. It is not
necessary or advisable to wait until the five year program is over to start
transferring system responsibility to the state. The transfer should begin as
soon as the state's commitment has been secured.
Several programs commented on the complexity of securing funding for data
management and how the program is handling this challenge:
Casco Bay: The program recognizes that it would be impossible to develop a
data management system specifically for the program, because the funding is
not available. The program's entire data management system is designed
around existing systems that will be maintained by the EPA. The ODES/GIS
application, developed with headquarters funds and contractor support, is
simply a front-end to these systems and functions as a data integration tool.
Workshop Summary 17
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Buzzards Bay: The program's goal is to build up the capacity of the state
technical and data management expertise, so that it can take over the system.
However, the state is not in a financial position to do that, so realistically the
program will only have enough money for long-term monitoring. Even a
few of the data collection projects that were established during
characterization will not become part of the long-term monitoring program
due to lack of funds. The program is currently trying to obtain support from
other sources.
Sarasota Bay: The program hopes that the data management effort will
uncover inefficiencies in the current Bay monitoring program. The data
managers need to review the data collection process to determine if the most
effective number of stations, times of day, and number of samples are being
included in the sampling program. If inefficiencies are discovered, the
program feels that the amount of money spent on monitoring will decrease
in the long run.
2. Functional Requirements and Documentation
Functional requirements are statements of what the data management system
needs to do, not how the systems accomplish the processing. The functional
requirements of the system are affected by a variety of factors including the
need for system flexibility. As priorities in the program shift, the data
management system must be able to accommodate those changes. Some
programs are designing systems in an "ad hoc" manner. In this situation, a
program manager indicates that he or she needs to access a particular data set
or to answer a specific question. In response to the request, the data managers
formats data sets, or writes a case specific application. Responding to requests
on a case by case basis is costly in the long run, because all of the data sets are
not formatted consistently and subsequent applications need to manipulate
diverse data sets.
Documentation created to support the system is an important factor in the
success of the system. The documentation can explain the people's roles,
system procedures, needs and functional definitions. The documentation
serves as a baseline for verifying the system design and should be reviewed
periodically. In addition, the system platform should be documented, so that
the data can be easily shared among different systems. For example, extensive
documentation of the ODES and STORET platforms facilitated the
development of a link between the two systems (i.e., the ODES/STORET
Bridge).
There is detailed data management systems design methodology
documentation available from OIRM. However, the NEPs do not have the
time or the financial resources to go through the step-by-step life-cycle. The
Workshop Summary
18
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OIRM methodology must be tailored to meet the NEP needs. In fact, NEP
needs will differ for each program.
3. Identifying a Successful Data Management System
Even if the system design and documentation are perfect, the system is still
not guaranteed to be a success. A system can only be successful if it fits into
the way people perform their assessments, characterizations, and analyses.
Success can only be achieved fully if these people are involved in the design
stages above. Basic question should be asked to examine a system's success,
such as:
1) How many CCMP improvements did the system provide?
2) Did any policies or decisions result from the use of the system?
3) How often is the system being used?
4) Were all targeted users served?
Workshop Summary 19
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IV. Small Group Discussion of Data Management Issues
The Workshop participants were divided into three groups to discuss data
management issues. The groups were arranged to mix representatives from
different tiers and programs. Appendix A includes the breakdown of group
members. Four topics were covered by each group: 1) data collection
methodologies, 2) QA/QC of data, 3) hardware/software alternatives, and 4)
tools for analyzing monitoring data. After the groups met for approximately
an hour and a half, a spokesperson presented the main ideas discussed in the
group.
A. Data Collection Methodologies
1. Group #1 Discussion
The data collection methodologies discussed in group #1 were very diverse.
Representatives from three programs identified the methodology currently in
place to collect data:
Albemarle-Pamlico: Data managers from North Carolina and Virginia met
after three and a half years to develop an inventory of data. In addition, a
data needs survey was developed and 65 data layers were agreed to be
collected. The data managers decided on the priorities for collecting the data
layers and assigned responsibility for collecting them.
Galveston Bay: The program decided that the existing state and federal
monitoring data is adequate for its needs, although all data prior to 1980 has
been lost. The data managers meet to develop overall goals for data
collection, and ad hoc planning is used to better define the data collection
methods within the goals.
Narragansett Bay: The Science and Technical Committee has identified areas
of data that need to be collected. The program has funded studies to collect
data to fill in the identified gaps. The program has hired experts to research
and assess the available data. The data managers have identified the types of
GIS coverages that the program needs, and have started to build them.
However, the coverages are being built without the end products in mind. So
far, this method has not led to any problems.
The group discussed what they felt the perfect methodology would be for
collecting data. In general, the group acknowledged the importance in
specifically stating the expectations of collecting data in the form of a
Workplan. A schedule of deliverables should be established, so that the
program receives the data on a timely basis. In addition, the required QA/QC
procedures should be stated at the onset of the contract. The QA/QC
Workshop Summary
20
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information reported to the program should include (at a minimum) the
sampling methods, laboratory methods, and QA data (e.g., blanks, spike
recovery).
In addition, the group decided that there are two options for developing a
request for proposal. First, the program can make the RFP very specific. This
option should be chosen when the requirements need to be explicitly stated.
Second, the RFP can be fairly broad. Developing a general RFP allows the
program to assess the contractor's understanding and expertise as related to
data collection and program objectives.
2. Group #2 Discussion
Every program in the group had different methods and protocols and
indicated that achieving consistency among the agencies involved with data
collection would be difficult. One example of data consistency among
agencies is in Florida where the state legislature requires that all data follow a
Quality Assurance Program Plan. In addition, the programs commented that
using ODES formats is another example of an effort to achieve consistency
among different agencies. Several group members offered comments about
the data collection methodologies in use in specific programs:
Long Island Sound: The program is following general data collection
protocols developed by the State University of New York and the University
of Connecticut. Currently, protocols are being developed by the state which
the program will follow. In addition, the program is planning to document
its data collection strategy.
Galveston Bay: The program has devised a bay segmenting scheme.
Currently, they are revising the sampling plan by evaluating the stations
being sampled. The analytical methods used to collect data are not
standardized. The strategy of the program is to coordinate the collection of
the data, and to distribute the responsibility for the data. The program is not
planning to centrally store the data.
Barataria-Terrebonne: Multiple monitoring programs are going on in the
estuary. Different methodologies and parameters are being used for each
monitoring program. The managers for the monitoring programs are not
coordinating the data collection efforts. Standardized protocols need to be
developed for the program. At this time, a variety of spatial data is also being
collected by the program, but specific conventions are not being followed.
Indian River Lagoon: Florida has imposed lagoon-wide Surf Water
Improvement and Management (SWIM) legislation which incorporates
monitoring at fixed stations throughout the lagoon. Formats for data
collection are established. The Indian River Lagoon Science Information
Workshop Summary 21
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system contains a bibliography and index of the data and QA/QC information
for the program. The QA/QC procedures will be reviewed i the near future.
Tampa Bay: Tampa Bay is a SWIM region, thus there are legislative
requirements to monitor the bay and submit the data to STORET. The
program has planned a Workshop for this summer to better coordinate the
collection and submission of monitoring data for the bay. Thus, the estuary
program is acting as an agent for improved coordination and cooperation.
Albemarle-Famlico: QA/QC reports are generally available through the
appropriate department for historical monitoring data. New monitoring
procedures are specifically stated in proposals prior to collection. Formats and
parameters for water quality data have been previously decided. The data
management staff visit the Pis to review formats and parameters when
necessary.
Delaware Estuary: A program study is currently underway to summarize the
variety of data types and collection methods being used. The state agencies
have consistent long-term data conventions, but the data is not centrally
stored. Bibliographic references are available, and the program is currently
considering ODES formatting conventions.
3. Group #3 Discussion
The group identified several common data collection problems which are
related to contractor management. Often contractors do not complete the data
collection on time. In addition, the money on the contract runs out before
the contractor makes any corrections to the data or provides adequate QA/QC
information.
The group offered some ideas to solve these problems. Specifically, the
contracts should specify data formats, QA/QC requirements, and a schedule
for delivery. In addition, the final payment should be held until all data is
submitted in the correct format and all QA/QC information is completed.
The group added that a program person needs to be appointed to specifically
oversee the data collection contract. This contract manager should verify that
the data is collected in the correct format with adequate QA/QC information
and in a timely manner.
Workshop Summary
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B. QA/QC of Data
1. Group #1 Discussion
The group identified the QA/QC procedures in place for the individual
programs:
Galveston Bay: QA/QC information is available for some historical data. The
program is currently screening the QA/QC for all data sources to collect
information concerning how and when the data was collected. Before any
new data is collected, a QA/QC plan must be established before. The EPA
requirements for QA are generally followed, however, they often must be
supplemented to provide the level of detail necessary.
Albemarle-Pamlico: The three agencies collecting data for the program are
coordinating their QA/QC efforts including participating in workshops.
Narragansett Bay: New data collection projects must have QA/QC plans that
follow EPA guidance. These plans are submitted to the EPA Regional office
for review. The program data managers are beginning to develop QA/QC
guidance for data collection.
During the group discussion, there was considerable concern about how to
ensure that the data collected by contractors was submitted in a complete,
accurate and timely manner. The group generally agreed that peer reviews of
the data work well to detect any problems with the accuracy or data collection
methods. In addition, the contract for data collection should require that the
data be delivered according to a set schedule and that the complete payment
for the work should not be made until the data and QA/QC report are
submitted.
2. Group #2 Discussion
The group decided that although different data collection methods and
protocols are used by individual agencies, information about the methods
and protocols must be referenced. In addition, more of an effort needs to be
placed on making this information available in electronic form, similar to the
on-line QA/QC reports in ODES. For example, Puget Sound uses a grading
process to denote the quality of its data. Instead of storing spikes and blanks
on-line, a number from 1 to 5 is associated with the data to indicate the
relative quality of the data.
3. Group #3 Discussion
The group discussed the roles in the QA/QC process and decided that the PI
performs the quality control procedures, and the data base manager performs
Workshop Summary 23
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the quality assurance procedures. Specifically, the PI collects the data and
verifies that the procedures are appropriate and accurate. The PI should
provide information concerning blanks and spikes associated with the data, as
well as a description of how the collection instruments are calibrated. The PI
should also provide information on any notable trends in the data. After the
PI provides the data and the quality control information, the data manager
should then review the data to make certain that it is in the correct format
and that all required quality control checks have been performed and
documented.
The group strongly agreed that documentation is the key to the QA/QC
process. Each data set must be documented as completely as possible. Data
should never be discarded. Even if no information exists about the data,
document that fact. Providing as much documentation as possible allows the
user to judge whether or not the data is useful in his or her studies.
QA/QC methods used by several programs were discussed during the group
session:
Narragansett Bay: The data managers perform frequency distributions and
range checks on the data. Standard method codes and sampling codes are
used across data sets. A text file is associated with each data set which
includes contact information for the data. The text file is updated to describe
how and when a data set is used.
Casco Bay: The program's technical committee is developing standards for all
newly collected data. The program is "double checking" its QA/QC process by
first performing their own review of the data, then sending the data to the
ODES technical staff for its QA/QC review. The program is then comparing
their own results with that of the ODES technical staff.
Santa Monica Bay: At a minimum multivariate analyses are run on the data
set to check QA/QC across the variables. A manual of quality control
procedures has been developed, but each data set requires additional review
in addition to the standard procedures.
C. Hardware/Software Alternatives
1. Group #1 Discussion
The hard ware/software in use by the program was discussed:
Sarasota Bay: The principle investigators (Pis) use their own hardware and
software when collecting the data. The program receives disks in ASCII
format and hard copies of the data from the Pis.
Workshop Summary
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Galveston Bay: The Pis collecting data use a variety of hardware and software,
and the Pis submit the data in ASCII format.
Narragansett Bay: The program decided to use FOCUS, a commercial data
base management software package, for its data management system mainly
because this software was already in use by the state. The system has worked
very well. However, FOCUS and ARC/Info are not on the same hardware
platform, so issues have arisen when they have tried to use ARC/Info with
the program data. They are currently running their system on a VAX, but
stress that there is no one hardware and software solution.
2. Group #2 Discussion
The group reviewed Section IX in the notebook which included an overview
of the hardware and software in use by each program. In addition, the group
discussed the necessity of considerable disk space to manage the quantity of
data needed by the programs. Specifically, when programs analyze land use
data, multiple gigabytes is required.
3. Group #3 Discussion
Each program in the group is using a different combination of hardware and
software for its data management effort, as demonstrated by the overview of
hardware and software in Section IX of the notebook. Most programs took
advantage of what ever was available to them from the state or universities.
In some programs, such as Casco Bay, the state is providing funding for all
hardware and software the program requires.
In general, the programs are satisfied with the hardware and software that is
available to them. The group stressed that one of the most important features
of the system is to allow data to be stored in a central location so that it can be
downloaded to a personal computer. Downloading the data allows an analyst
to use his or her favorite software to perform the analyses. Of equal
importance to the programs is the need for significant computer power to
manage the large data bases being developed.
D. Tools for Analyzing Monitoring Data
1. Group #1 Discussion
There are a variety of tools in use by the programs for analyzing monitoring
data. Similarities exist among the programs relating to the types of analysis
being conducted, but there are differences in the actual logistics of how the
analyses are accomplished:
Workshop Summary 25
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Albemarle-Famlico: The program is primarily focusing on using its GIS for
analyzing the monitoring data, and the system is working well. Issues have
arisen because the GIS applications do not provide the capability to perform
statistical routines such as correlation and regression.
Sarasota Bay: The program is using its data to perform trend analyses.
Narragansett Bay: Contractors are performing statistical analyses such as
time-series and cluster analyses. However, it is difficult to correlate causes
and effects. The program is now focusing on data modeling, and is drawing
on the index of available data to develop the models.
Galveston Bay: Highly customized models have been developed for the
estuary. Contractors are required to use and contribute to the data base
inventory, bibliography and literature search.
2 Group #2 Discussion
The group discussed the broad range of models used by individual programs.
Some programs have the facility to run a model and capture a specific "time
slice" and store the information as a coverage in a GIS. Other programs have
models which produce numerical coefficients that are incorporated into
reports.
3. Group #3 Discussion
The programs in the group, including the Tier I estuaries, have not begun to
analyze the data being collected. The data managers are collecting and
documenting data, so that studies can begin. Some programs, including Long
Island Sound and Santa Monica, have tasked contractors to perform small
studies when needed.
Among most of the programs in the group, a general lack of objectives for
data use exists. The program has not specifically identified why the data is
being collected. As a result, thousands of dollars is spent on data collection,
but no one is using the data for analysis. On the other hand, Christopher
Kroot from Casco Bay explained to the group that the program would not
commit to collecting any data until the data managers and program managers
decided on what tools would be available. He stressed that this method has
worked very well.
Workshop Summary
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V. National Data Management System Resources
Three national data management systems were presented. Gary Labovich
discussed the ODES/STORET Bridge, Craig McCulloch presented COMPAS,
and Christopher Kroot explained the benefits of the ODES/GIS Connection.
In addition, Tom Gulbransen briefly discussed the NEP Inventory and
requested additional information from the Workshop participants.
A ODES/STORET Bridge
Gary Labovich - American Management Systems, Inc
1. What is the ODES/STORET Bridge?
The ODES/STORET Bridge is a user-friendly link that connects the ODES
system and the STORET data base. The Bridge provides access to water quality
data stored in STORET through the menu-driven facilities of ODES. The
purpose of the bridge was to eliminate the need for a user to leave the ODES
system to access STORET data.
2. How has the ODES/STORET Bridge Evolved?
The bridge was originally designed to provide user-friendly menus to access
STORET data. A Basic Option was added to the ODES system, Basic Option S,
which helps users identify STORET agency codes, station codes, and available
dates for data. An additional goal for the Bridge was to allow users to access
more data for analysis. However, the ODES system creates a geographical
boundary for a program, so users can only access data collected within a
program's boundary. A geographical boundary may be increased or reduced if
necessary.
The Bridge was also created to give users access to historical data maintained
in STORET when recently collected data is stored in ODES. In addition, the
Bridge provides graphical tools that can plot STORET data, and the ability to
download STORET data in text or ARC/Info format.
Estuary Programs have requested enhancements to the Bridge, so users can
access all STORET estuarine water quality parameter codes associated with the
data collected for the program. In addition, the enhanced Bridge will access
all variables associated with STORET estuarine water quality data. The
downloading feature will be expanded to handle all STORET estuarine
parameter codes and variables.
Workshop Summary 27
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3. How can the Estuary Programs use the ODES/STORET Bridge?
Estuary Programs can use the enhanced ODES/STORET Bridge in a variety of
ways. For example, user-friendly menus will prompt a user to identify a
subset of STORET data. Users can select data by station attributes (e.g., within
Delaware or by "ESTURY" station type), and can select data by sample
attributes (e.g., by time ranges or depths). In addition, any STORET estuarine
water quality data may be downloaded in text or ARC/Info format, and
reports of any STORET estuarine water quality data can be created.
4. How does the ODES/STORET Bridge Relate to the NEP Data
Management Policy?
The enhanced ODES/STORET Bridge provides complete access to estuarine
water quality data for OWOW. As a result, OWOW is considering amending
the NEP Data Management Policy. The amended policy would allow water
quality data to continue to be submitted to STORET instead of ODES, if the
program currently submits its water quality data to STORET. If the policy is
amended, it will not apply to biological data. The requirement to submit all
biological data generated with NEP funds to ODES would remain in effect.
OWOW is currently using the state of Florida as a test case to determine if this
policy should be amended. Florida has been chosen as the test case because
the state requires all water quality monitoring data to be submitted to
STORET. Under this test case, a data description form will be required for
each water quality data set submitted to STORET. The data description form
will require the program's data managers to provide a QA/QC description
including the goals of sampling program, station descriptions, and sampling
techniques. Each form will be reviewed by ODES Technical staff, and a
QA/QC report will be stored on-line in ODES.
Workshop Summary
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B. NEP Inventory
Tom Gulbransen - Battelle Ocean Sciences
The data management representatives revised the overview of estuary
program hardware, software, and documentation located in the Workshop
notebook. The following chart indicates the diversity among estuary
programs in the hardware and software being used, the number of people
dedicated to data management support, and the documentation that has been
produced.
Program
Chesapeake Bay
TIER I
APES
Buzzards Bay
LISS
Narragansett
Puget Sound
Hardware
PC's
Workstations
VAX
Data General-5+
Sun Workstations
(> Gigabyte)
PE
VAX-State
NCC
VAX-University
State Systems
PCs
MicroVaxII
Prime-Unix
VAX-EPA Lab
(University)
Software
ARC/INFO
Models
DBs
Custom
SAS
Image /Vid.
ARC/INFO
STORET
ERDAS
SAS
ISM
ARC /INFO
ORACLE
SAS
Models
Paradox
Focus
ARC /INFO
Custom
People
Involved
30
1
Part-time
1
Part-time
<4
Distributed
Documenta-
tion
Index
Data Transfer Doc.
Data Dictionary
Bibliography
Data Mgt. Plans
Needs Assessment
Data Dictionary
Functional
Description
Data Mgt. Plan
Data Reqrmts.
System
Description
System Design
Needs Survey
Data Index
Index of Data
Needs Survey
User Manual
Data Submissions
Manual
SOPs for System
Maintenance
Needs Assessment
Data Transfer
Specs
User Manual
Bibliography
Workshop Summary
29
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Program
San Francisco
TIER II
Delaware Bay
Delaware Inland
Bay
Galveston
NY/NJ Harbor
Santa Monica
Sarasota Bay
TIER III
Barataria-
Terrebonne
Casco Bay
Indian River
Mass Bay
Tampa
Hardware
MicroVAX
-
PC
Workstation-St.
VAX-St.
PC's
(University)
-
-
MVIOK DG (St.)
Workstation
File Server
Workstation
PCs
VAX-State
PCs
Software
Info
Custom
-ODES
ARC/INFO
ORACLE
Custom
STORET
-COMPAS
-ODES
Custom
TRAKS (state)
-ODES
Distributed
-ODES
ARC/INFO-State
MARS
MOSS
ERDAS
Integraph
ARC/INFO
-ODES
-ODES
STORET
ARC/INFO
ORACLE
-ODES
STORET
People
Involved
<2
Part-time
=2
Part-time
Distributed
Part-time
~2
"1/2
1
Documenta-
tion
User Manuals
Monitoring Plan
-
Preparing Design/
Dev
(User Manual?)
Plan
Index
Bibliography
Data Mgt
Strategy
Data Inventory
Data Mgt. Needs
Assessment
Draft Strategy
System Design
Data Mgt. Plan
-
-
Workshop Summary
30
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C. NOAA Systems (COMPAS)
Craig McCulloch - Texas Water Commission
1. What is COMPAS?
COMPAS is a desktop information system which integrates maps and
graphics. As a desktop information system, COMPAS provides a
microcomputer based system which is highly focused for the user. The
system allows direct access to the data as well as simple, interactive operations
and powerful analytical capabilities.
COMPAS runs on an Apple Macintosh n and incorporates several
commercial software packages. HyperCard provides the graphical front-end
for the system. ORACLE, a relational data base, maintains and manipulates
the data behind the front-end. MapMaker displays geographic information
on maps. Although MapMaker is not as sophisticated as ARC/Info, it is
adequate for the system's mapping requirements.
The following modules are currently being developed in COMPAS.
1) Physical & Hydrologic
2) Recreation
3) Non-point Sources
4) Wetlands Permits
5) Land Use
6) Marine Resources
7) Point Sources
8) Facilities
9) Habitats
10) NOAA Monitoring
11) Shellfish Growing Waters
12) Housing & Population
13) WQ Monitoring
14) Coastal Tracts
15) Water Rights
16) Streamflow Gages
COMPAS also provides estuarine models. These models including two-
dimensional steady-state estuarine models that can allow users to study
salinity or conservative and non-conservative water quality pollutants.
2. Who is Developing COMPAS?
The first twelve modules listed above primarily contain NOAA data. The last
four modules are being developed with data from Texas. Many groups are
involved in developing these four modules including: Texas Water
Workshop Summary 31
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Commission, Department of Health, Parks and Wildlife, General Land Office,
Texas Natural Resources Information System, Water Development Board,
Railroad Commission, and the University of Texas' Bureau of Economic
Geology.
The data collected to be maintained in the system is being reformatted to a
predefined standard. To eliminate the amount of reformatting, the system
developers are trying to identify the specific data that is actually used in the
decision making process and provide that data in COMPAS. For example, if
summary statistics are used for the analysis, only those statistics are stored in
the data base. The entire wealth of source data is maintained on the
mainframe.
3. Examples of COMPAS Modules
Each module provides the user with a variety of options. For example:
The Marine Resources module presents the temporal distribution and
relative abundance for a specific taxa in an estuary. Pull down menus
easily allow the user to select a different taxa or estuary.
The Water Quality Monitoring module allows a user to select a specific
monitoring station. COMPAS displays summary statistics for the
monitoring data available for the selected station and time period. The
user can easily select a different station, time period, parameter group,
or statistic using the pull-down menus.
A user identifies a study area in the Coastal Tracts module and
retrieves a map of the area displaying all of the monitoring stations.
The user can then select a specific station in the study area, and
COMPAS will display summary statistics for the the monitoring data
that has been collected at that station.
Workshop Summary
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D. ODES/GIS Connection
Christopher Kroot - Casco Bay Program
1. Why Maine Chose ODES & the ODES/GIS Connection
When the Casco Bay program started, managers and scientists evaluated the
ODES system as an option for managing the data collected for the Bay. The
program decided to use ODES because the system maintains a substantial
amount of data, has a flexible data structure, and is integrated with a GIS
application, the ODES/GIS Connection. In addition, the managers and
scientists agreed that ODES provides the analytical capabilities to meet most of
their needs. If the application does not meet their needs, they can download
the data and use the file in any commercial software package (e.g., Lotus 1-2-3,
SAS).
2. Tailoring the ODES/GIS Connection for Maine
The scientists and managers from different agencies in Maine were involved
in the design and development of the ODES/GIS Connection application. As
a result, the system design specifically meets their needs. The GIS will
provide easy access to data for the public, state agencies, environmental
groups, universities, and local governments. Approximately 22 agencies are
involved in developing Maine's system. By allowing the agencies to be
directly involved in the design and development of the system, the agencies
have a greater interest in ensuring that the system continues to be supported.
The state has developed the majority of the data. In addition, the program
has been working with OWOW and AMS to develop the menu-driven
interface for the ODES/GIS Connection for about a year. It has been a
challenging project because many groups are involved in developing the
system. Each group has its own set of expectations from the system, and only
a limited amount of money is available to apply towards the contract with
AMS to develop the system. The program feels that they have been
successful in negotiating compromises among the groups to provide the best
system possible to meet each groups needs.
3. How the ODES/GIS Connection Works
The key to the ODES/GIS Connection is the menu-driven interface, because it
allows someone who does not know any thing about computer programming
to easily use the system. The interface consists of a series of general headings.
The general headings are pull down menus which allow a user to select
monitoring programs, file types, parameters, and date ranges.
The "Draw" menu prompts the user with a list of available data coverages
such as shellfish beds, marine water quality sampling stations, critical
Workshop Summary 33
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habitats, and non-point source dischargers. Any additional coverages can be
included in the application. The user can review the list of available data
layers and select the specific overlays of interest. The ODES/GIS Connection
also provides a dynamic legend which displays the specific coverages that user
selected and the corresponding color and shape.
The system resides on the EPA prime, but it will be ported onto Maine's SUN.
The base ODES/GIS Connection application is designed to be hardware
independent, thus it can run on any program's hardware.
Data from PCS, ODES, STORET, or other systems is downloaded once a week
or month (depending on the frequency of data updates) to a floppy disk or
tape. The data is then uploaded into the ODES/GIS Connection application.
Once the application is completed, Maine will look into developing
communication links to these systems similar to the ODES/STORET Bridge.
However, at this point developing those communication links is too
expensive.
Anyone that has access to the EPA computing network will be able to access
the application in the future. The user only needs to obtain a modem and a
communications software package that emulates a techtronic terminal. The
EPA is committed to helping other programs use this software. EPA and
Maine's purpose in developing the ODES/GIS Connection was not to give
Maine a specialized tool, but to develop an application that can be used by
other programs. When the menu-driven interface was designed and
developed for the state of Maine, it was particularly challenging to design a
user-interface that would be specific enough for Maine, but also general
enough to be used by other programs. However, the generic design has been
successful, and the application can be tailored to meet the needs of any
program.
4. How Maine is Using the ODES/GIS Connection
The Department of Environmental Protection will be using the menu-driven
system to manage most of its GIS related data. The data base will soon
include information from AIRS, PCS, STORET and ODES. As a result, an
analyst is not limited to one type of information. The Casco Bay program is
fortunate that the senior management in the Department of Environmental
Protection are committed to cross-media applications. The managers
recognize the importance of making natural resource decisions by evaluating
the "big picture".
Maine is also planning to use the ODES/GIS Connection application for
evaluating the state's watershed. Maine has a considerable amount of non-
point source information that is currently being incorporated into the menu-
driven system.
Workshop Summary
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The state of Maine is one of three states that has a mandated Growth
Management Comprehensive Planning Law where all towns and
communities must develop a plan for pollution prevention and growth
management. Local officials in the towns in Maine, especially in the water
districts, recognize that the ODES/GIS Connection will provide them with
access to zoning and growth management information.
Workshop Summary 35
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PLANNING AND PUTTING IT ALL TOGETHER
I. NEP Data Management Policy: Review - Mark Curran
A. Need for an NEP Data Management Policy
A significant portion of the funds provided by the National Estuary Program
are spent on information management. The EPA has the responsibility for
maintaining and providing access to the information collected as part of the
NEP. As a result, the EPA has established a data management policy which
requires all data generated with NEP funds to be submitted to a central data
system, the Ocean Data Evaluation System (ODES), so that the data can be
maintained on a national level. Please note that the policy does not require a
program to use ODES for analysis.
The EPA chose ODES as the central data storage system for many reasons.
Specifically, the system is agency approved and supported. ODES cost four
million dollars to develop, and continues to be supported through EPA
funds. In addition, ODES is fully developed and has been in use since the
beginning of the 301 (h) program. The system provides data accessibility at a
national level. The ODES data submissions process incorporates QA/QC
procedures, so that the data maintained is of the highest quality possible. The
ODES Technical Staff reviews the data and prepares a QA/QC report which is
stored on-line in the system. In addition, the system uses consistent formats
for data which will allow EPA, or anyone, to analyze data across programs or
study areas.
B. Issues Resulting from the Policy
The EPA recognizes that this policy raises many concerns for estuary
programs. For example, older programs were putting data on the NCC
mainframe using NODC codes. To address this problem, the EPA asked the
Tier I estuary programs to identify priority data sets. EPA would pay the costs
for converting the data sets to ODES, if the program was going to use ODES as
its data management system.
Historical data presented additional issues related to the policy. Data that was
collected prior to the 1990 fiscal year is not required to be submitted to ODES.
However, if a program chooses to use ODES as its data management system,
this data would likely need to be converted to the same format as the newly
collected data. The programs have the responsibility for reformatting the
historical data.
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EPA recognizes that this policy may require the creation of new ODES file
types. A survey was distributed to all estuary programs soliciting their needs
for ODES file types to accommodate the program's data. Although the
summary results are inconclusive, it seems that a file type related to non-
point sources needs to be developed. However, the specific parameters to be
stored for non-point source information are difficult to pinpoint. As a result,
the specific requirements of the non-point source file type need to be focused.
ODES is not a static system. It is flexible and can accommodate new file types
as well as changes to existing file structures.
One of the largest issues resulting from the policy relates to the cost of using
the ODES system. Specifically, the management conference has the
responsibility for formatting the data for ODES. EPA recommends that the
programs include this stipulation in the contracts established with Pis. Once
the data is submitted to ODES, EPA pays the cost for the QA/QC process and
loading the data into ODES.
When the policy was originally established, the EPA felt the need to disperse
the ODES system usage fee among the programs. However, the $20,000 fee
per program per year inhibited the use of the system. As a result, the EPA has
assumed the cost of the ODES usage fees for the estuary programs. Please note
that the funds provided to support ODES usage for the NEP are taken from
the operating budget, not program funds. If a representative from a program
is interested in using the system, he or she simply needs to call the ODES
hotline to obtain a user ID and password for the NCC mainframe.
The EPA also recognizes that many programs have stored data in other
national data bases, specifically STORET, and need access to this data. As a
result, EPA has developed and is enhancing the ODES/STORET Bridge which
will provide access to all STORET estuarine water quality data.
C. NEP Support
The EPA intends to enforce this policy, but is committed to providing support
to assist programs in complying with the requirements. Contractor support is
available through the NEP from AMS, Tetra Tech and Battelle. General
information management support can be obtained from Battelle. ODES
support is available through AMS and Tetra Tech and includes, among other
things, hotline access and training.
The NEP Data Management policy does not apply to GIS data, however the
CIS National Program Office (GISNPO) can provide support to the NEP. The
GISNPO supports many activities to disseminate information and provide
assistance related to GIS applications. The program supports regional GIS
teams and an outreach program. The outreach program distributes a
newsletter and maintains a bulletin board system to help disseminate
Workshop Summary 37
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information. The program is in the process of distributing a survey to
identify training needs. Training courses should begin this summer.
GISNPO supports the GRIDS system which maintains national data layers
that have been developed by various agencies. These data layers can be
provided to other programs at no cost to the program. National mapping
requirements have also been identified by GISNPO. These requirements are
sent to the Office of Management and Budget to identify priority data layers
that should go on-line in the GRIDS system.
GISNPO is coordinating a spatial data management plan and a PC GIS study
to establish priorities and identify user needs. In addition, the GISNPO
worked with the Office of Policy Planning and Evaluation to conduct an
human health and environmental assessment among all 10 regions. For
additional information on this project contact Bev Martain.
The GISNPO can assist the NEP in its efforts to effectively use GIS and obtain
information about recent developments in GIS applications. The names of
NEP data managers should be added to the mailing list for the GISNPO
newsletter and to the bulletin board system. In addition, the GISNPO can
help facilitate GIS information exchange among the programs. For example,
sources of GIS support can be identified for a program. In addition, the
application of GIS to meet program requirements and objectives can be
explored and technical support can be made available.
Other participants highlighted several other sources of information that are
available to the NEPs:
The River Reach System provides hydrography and point-source
discharge information.
The Information Resources Directory is an index of all Office of Water
information systems that was developed by OIRM.
COASTNET is a bulletin board system that helps users disperse
information
D. EPA Data Management System Modernization
EPA is beginning a modernization effort to combine the existing water
management information systems. The modernization is currently in the
planning stages, and EPA is obtaining input from system users. A
symposium is planned for September where EPA managers are meeting to
identify issues to consider and to develop a preliminary modernization plan.
The new system will contain one data base to include all physical, chemical
and biological data. The system will be menu-driven and run on the IBM
Workshop Summary
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9000 with telecommunications and full technical support. The proposed
modernization effort will not produce a system that will be ready to test for at
least 4-5 years. In the interim, the EPA continues to fully support existing
systems, including ODES.
Workshop Summary 39
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II. Costs and Benefits of Data Systems Development
A. OIRM System Life Cycle Development Methodology &
EPA Approved Hardware/Software
Jean Sammon - Office of Information Resource Management
1. Life Cycle Management Series
OIRM has developed the Life Cycle Management Series which contains the
following documents:
Volume A - Mission Needs Analysis
Volume B - Preliminary Design and Options Analysis
Volume C - System Design, Development and Implementation
Supplemental Guidance to Volumes A and 6 - Guidance for
Developing Image Processing Systems in EPA
Supplemental Guidance to Volume B - EPA/APD Applications
Guidance to Hardware/Software Selection
Operations and Maintenance Manual
In addition to these documents, additional references are also available
through OIRM:
EPA Information Security Manual
NDPD Operational Policy Manual
ADABAS Application Development Procedures Manual
Guide to NCC Services
2. Importance of OIRM Documentation
These documents were developed to provide criteria for decision-making,
and to address project scope, planning and management. In addition, these
documents will help managers to clarify expectations and requirements of the
system to promote user involvement. Agency-wide standards are also
provided in these documents.
Workshop Summary
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These documents are important because millions of dollars are expended
each year on developing, operating and maintaining systems. As a result,
programs need to invest resources wisely from the beginning of the system
life cycle. Agency systems are becoming increasingly complex because more
emphasis is being placed on cross-media analysis, data integration and public
access. These complexities require improved focus on sound data
administration and for a systematic approach to defining needs and
developing applications.
3. Selecting EPA Approved Hardware and Software
There is a wide range of EPA approved hardware and software options to
consider. Selecting EPA approved hardware and software leads to increased
compatibility among EPA systems, the elimination of "Islands of
Technology", and the facilitation of data sharing. Significant benefits result
from selecting EPA approved hardware and software. For example, EPA
support is available for training, and hardware or software upgrades. In
addition, system-life cycle costs are reduced, because the hardware and
software has already been tested, and a pool of experts is available for
reference.
Workshop Summary 41
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B. Long-term Systems Maintenance and Operations - Issues
Gary Labovkh - American Management Systems, Inc.
1. Phases of the System Life Cycle
The system life cycle consists of four phases:
Needs Analysis/Preliminary Options
Detailed Design of the System Function
Software Development, Testing, Integration, Verification & Validation
Operations & Maintenance
2. Percentage Cost Comparison of System Life Cycle Phases
Reviewing the percentage cost comparison for System Life Cycle phases
indicates the relative importance of maintenance and operations within the
system life cycle:
Needs Analysis/ Preliminary Options - 5%
Detailed Design of the System Function -15%
Software Development, Testing, Integration,
Verification & Validation -35%
Operations & Maintenance - 45%
The operations and maintenance phase is the vehicle for preserving the
investment in the system. If managers do not adequately plan for operations
and maintenance, the system is doomed to failure.
3. Elements of System Maintenance and Operations
The first element of system maintenance and operations is system operation.
System operation includes activities such as assigning user IDs, updating
system dictionaries, and performing system back-ups. In addition, the system
and data base usage is continually monitoring, and minor system
enhancements are developed, implemented and tested. For a system to
operate most efficiently, someone should be appointed system administrator
to oversee the above activities.
Workshop Summary
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o
Technical user support is the second element of system maintenance and
operations. One component of technical user support is user training. For a
system to be optimally used, people need hands-on training. Training teaches
the user the most efficient ways to use the system. Informed users eliminate
the likelihood that he or she will submit useless batch jobs tying up the
system resources for others. Access to a user support hotline is an additional
component of technical user support. Providing this rapid response service
indicates to the users that the system support team is dedicated to making
certain they obtain the information needed. Hardware and software support
should also be a component of technical user support. If users cannot resolve
hardware and communications issues to access the system, they simply will
obtain the information they need elsewhere.
The third element of system maintenance and operations is developing
system documentation. When documentation is developed, it must be
geared toward the appropriate audience. For example, the ODES system has
four different documents, each developed for a specific purpose: 1) User's
Guide, 2) Data Submissions Manual, 3) Data Briefs, and 4) the Tool Manual.
After the documentation is developed, it must be updated as the system
changes and evolves. In addition, the system support team must develop a
plan to efficiently disseminate the documentation.
Implementing hardware and software upgrades and improvements is the
fourth element of system maintenance and operations. Any affected system
features must be modified to appropriately handle the new versions of
hardware and software, and the system must be tested thoroughly. In
addition, the documentation must be updated to reflect the system changes,
and the users must be informed of the system updates.
The fifth element of system maintenance and operations is debugging errors.
First, the source of the error must be identified. Second, the optimal solution
to the problem must be determined. Then, the system support team must
identify any effects from implementing the chosen solution, so that another
system feature does not crash due to the selected "solution". Finally, the
system must be thoroughly tested to ensure that the error is resolved.
The sixth and final component of system maintenance and operations is
evaluating major system modifications. When someone proposes a major
system change such as the ODES/STORET Bridge, the system support team
must determine if the modification will effectively solve the information
management problem. In addition, the team must determine it is the most
efficient way to solve the problem. A realistic evaluation of the extent of the
modification must be made to determine how long the modification will take
to implement and how much it will cost.
Workshop Summary 43
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4. Reducing Operations and Maintenance Costs
Several operations and maintenance benefits result from developing a system
using EPA approved hardware and software platforms. Specifically, the
hardware and software has already been tested, and a pool of experts already
exists for reference. In addition, training support is available, and support is
also available when hardware and software is upgraded.
It is important to note that system maintenance and operations begins after
the system is fully functional. Although this is the last segment, 45% of the
money spent during the system's life cycle is on system maintenance and
operations. As a result, system planners must consider the long-term
personnel and financial resources needed to support systems maintenance
and operations.
Workshop Summary
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in. Proposed Action Items
The Workshop participants were given the opportunity to identify types of
data management support that would be useful for the NEPs. The following
suggestions were made:
Develop a list of documentation that is available through the
individual programs, OWOW, and OIRM.
Prepare a summary of each program's data management strategy
including an assessment of how well the strategy is working.
Support the wide spread use of COASTNET to facilitate the
communication between programs.
Include the names of the Workshop participants on all program
newsletters.
Prepare a report documenting the QA/QC procedures in use by each
program including a technical analysis of those procedures.
Support additional opportunities for NEP program data managers to
meet to discuss program concerns, goals and objectives.
Workshop Summary 45
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Appendix A
Small Discussion Groups
Group
Facilitator: Mark Shibata
Note Taker: Carl Hanson
Spokesperson: Dave Tomasco
Name
1) Jenifer Steele
2) Stephen Hale
3) Mindy Lemoine
4) Russell Kiesling
5) Charlotte Schwartz
6) DaveTomasko
7) SueHawes
8) Dillon Scott
9) BUlMuldrow
Program/Organization Tier
Albemarle-Pamlico Estuarine Study I
Narragansett Bay Project I
Delaware Estuary Project n
Galveston Bay National Estuary Program n
Galveston Bay National Estuary Program n
Sarasota Bay National Estuary Program n
Barataria-Terrebonne HI
Massachusetts Bay Program in
OIRM
Group #2
Facilitator: Bob King
Note Taker: Tom Gulbransen
Spokesperson: Tom Gulbransen
Name
1) Tim Johnson
2) Sue Kenney
3) Frank Shipley
4) Ron Embry
5) Greg Du Cote
6) Holly Greening
7) Bob Day
8) Drew Puffer
9) Jean Sammon
Program/Organization Tier
Albemarle-Pamlico Estuarine Study I
Long Island Sound Study I
Galveston Bay National Estuary Program n
Galveston Bay National Estuary Program n
Barataria-Terrebonne in
Tampa Bay ffl
Indian River Lagoon HI
Gulf of Mexico Program
OIRM
Workshop Summary
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Group #3
Facilitator: Gary Labovich
Note Taker: Lisa Eunice
Spokesperson: Robert Smith
Name
1) Neil MacGaffey
2) Susan Smith
3) Cynthia Print-Ham
4) Bob McFarlane
5) Robert Smith
6) Craig McCulloch
7) Chris Kroot
8) John Piper
Program/ Organization
Buzzards Bay Project
Narragansett Bay Project
Long Island Sound Study
Galveston Bay National Estuary Program
Santa Monica Bay Restoration Project
Galveston Bay National Estuary Program
Casco Bay
Great Lakes National Program Office
Tier
I
I
I
Workshop Summary
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Johnson
Jennifer Steele
Appendix B
Appendix D
NEP Data Management Workshop Participant List
Albermarle-Pamlico Estuarine Study
512 N. Salisbury Street
Room 1125
Raleigh NC 27604
Albermarle-Pamlico Estuarine Study
P.O. Box 27687
(919) 733-2090
(919) 733-0314
Gary Labovich
Lisa Eunice
Rosem«try Watt
Carl Hcjison
Greg DiiCote
Sue Hawes
Raleigh NC 27611
AMS
1777 North Kent Street
7th Floor
Arlington VA 22209
AMS
1777 North Kent Street
7th Floor
Arlington VA 22209
AMS
1777 North Kent Street
7th Floor
Arlington VA 22209
AMS
1777 North Kent Street
7th Floor
Arlington VA 22209
Barataria-Terrebonne Estuary Program
Dept. of Natural Resources /Coastal Management
P.O. Box 44487
Baton Rouge LA 70804-4487
Barataria-Terrebonne Estuary Program
Corps of Engineers
P.O. Box 60267
New Orleans LA 70160
(703) 841-6970
(703) 841-6032
(703) 841-5513
(703) 841-6873
504-342-7936
504-862-2518
Tom Gtilbransen
Neil MacGaffey
Battelle
Ocean Sciences
397 Washington Street
Duxbury
MA
Buzzards Bay Project
Mass. Coastal Zone Management
100 Cambridge Street, Suite 2006
Boston MA
02332
02202
617-934-0571
(617) 727-9530
Workshop Summary
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Christopher Kroot
Mindy Lemoine
Russell Kiesling
dixB
Appendix is
NEP Data Management Workshop Participant List
Casco Bay
Maine DEP State House
Station #17
Agusta
ME
04333
Delaware Estuary Project
EPA Region III
841 Chestnut Street
Philadelphia PA
19144
Galveston Bay National Estuary Program
University of Houston-Clearlake
2700 Bay Area Blvd Box 164
Houston TX 77058
(207) 289-4292
(215) 597-3697
(713) 283-3950
Frank Shipley
Galveston Bay National Estuary Program
University of Houston-Clear lake
2700 Bay Area Blvd Box 164
Houston TX 77058
(713) 283-3950
Craig McCulloch
Galveston Bay National Estuary Program
Texas Water Commission
P.O. Box 13087
Austin TX 78711
(512) 371-6356
Robert McFarlane
Galveston Bay National Estuary Program
McFarlane & Associates
9503 Sharpview Drive
Houston TX 77036
713-772-8294
Charlotte Schwartz
Galveston Bay National Estuary Program
Texas Natural Resources Information System
P.O. Box 12321, Capitol Station
Austin TX 78711
(512) 463-8402
RonEmbry
Andrew Puffer
Bob Day
Galveston Bay National Estuary Program
Baytown Refinery - Exxon USA
P.O. Box 3950
Baytown TX 77522
Gulf of Mexico Program
Building 1103, Room 202
John C. Stennis Space Center
Stennis Space Center MS
Indian River Lagoon
1900 S. Harbor City Blvd.
Suite 109
Melbourne FL
39529
32901-4749
(713) 425-3333
(601)688-3726
(407) 984-4950
Workshop Summary
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thii Pring-Ham
Appendix B
Appendix i>
NEP Data Management Workshop Participant List
Long Island Sound Study
U.S. EPA Region I
WQE425 JFK Building
Boston MA
02203
617-565*4437
Sue Kennedy
Long Island Sound Study
Connecticut Department of Environmental Protection
122 Washington Street
Hartford CT 06106
(203) 566-6690
Dillon :5cott
Massachusetts Bays Program
100 Cambridge Street
CZM
Boston MA
02202
(617)727-9530 ext415
Susan Smith
Stephen Hale
Naragansett Bay Project
EPA Environmental Research Lab
27 Tarzwell Drive
Narragansett RI
Narragansett Bay Project
291 Promenade Street
Providence
RI
02882-1198
02908-5767
(401) 782-3044
(401) 782-3044
"ean Sammon
Bill Muldrow
Mark Curran
Joel Saher
Bob Kinjj
OIRM
401 M Street, S.W. Mail Code: PM-211D
Washington D.C. 20460
OIRM
402 M Street, SW
Mail Code: PM-218D
Washington DC 20460
OWOW
U.S. EPA Fairchild Buflding
401 M Street, S.W. Mail Code: WH-556F
Washington D.C. 20460
OWOW
U.S. EPA Fairchild Building
401 M Street, S.W. Mail Code: WH-585
Washington D.C. 20460
OWOW
U.S. EPA Fairchild Building
401 M Street, S.W. Mail Code: WH0556F
Washington D.C. 20460
(202) 382-5914
(703) 883-8878
(202) 475-8483
(202) 475-8484
(202) 475-7119
Workshop Summary
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Robert Smith
Dave Tomasko
Appendix B
Appendix D
NEP Data Management Workshop Participant List
Santa Monica Bay Restoration Project
EcoAnalysis, Inc.
221 East Matilija Street, Suite A
Ojai CA 93023
Sarasota Bay National Estuary Program
1550 Ken Thompson Pkwy
Sarasota
FL
34236
(805) 646-1461
(813)361-6133
Holly Greening
Tampa Bay Estuary Program
111 7th Avenue South
(813) 893-2765
Mark Shibata
Ken Green
St. Petersburg
FL
Tetra Tech
3746 Mt. Diablo Boulevard
Suite 300
Lafayette CA
VigYan, Inc.
5203 Leesburg Pike
Suite 900
Falls Church VA
33701
94549
22041
(415) 283-3771
(703) 931-1100
Workshop Summary
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Appendix C
Summary of Participants' Evaluation Sheets
This appendix summarizes the comments offered by the participants from the
NEP Data Management Workshop held in New Orleans, Louisiana on May 20-21.
There were approximately 40 participants from the various estuary programs, the
Great Lakes program, the Gulf of Mexico program and OIRM. The participants were
generally pleased with the Workshop, as demonstrated by the comments presented
below. These comments summarize 18 evaluation forms. (5=excellent)
Numerical Ratings: Average
1) Overall format of conference 4.2
2) Relevance of topics discussed 4.2
3) Time allowed for discussion 4.3
4) Opportunity for interaction among 4.4
participants
5) Emphasis on Estuary Program 4.0
concerns
6) Conference facilities 3.8
The following is a summary of the comments made to the following questions:
What additional information, relative topics discussed, would you like to have seen presented?
How OWOW is interacting with other media program offices
Evaluation of how well different programs are working
NOAA- Weather/Meteorological data and systems
None
Which session formats (i.e. panel discussions, small group discussions, etc.) do you
think were most effective?
The small group discussions were very popular
Generally people liked the mixed format of panel discussion and
small breakout group discussion
Workshop Summary C-l
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What is the single most important role OWOW should undertake to support the
transfer of information among those involved with the National Estuary Program?
Keep programs informed on state of the art program designs (i.e.
what is successful and provide technical assistance to deal with the
challenges).
Repeat the data management workshop annually
Expansion/improvement of tools which access/analyze/manipulate
ODES data.
Simply being there
Get STORET/ODES modernized
Newsletter to help facilitate Data Base Management information
exchange
"Demand use of COASTNET' and develop an 800 number
Do you see a need for other types of conferences?
Yes, monitoring program designs and their relationship to Data Base
Management.
Funding solutions after the NEP
Modeling in the NEPs-is it worthwhile?
Yes, the data management conference should continue
Activity which stresses transfer of relevant, summary info to
managers/decision makers.
What suggestions do you have for future NEP data management meetings (e.g.
format location, participants, etc.)?
Same type of format, same participants on a yearly basis
More working on-line Data Base Management demonstrations
Emphasize more case studies (i.e. programs with completed
characterizations)
Workshop Summary
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