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.
Workshop  Summary

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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.
Workshop  Summary

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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
Workshop  Summary

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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.
Workshop  Summary                                                      12

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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:
Workshop  Summary
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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.
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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.
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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.
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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.


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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
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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?
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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
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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
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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.
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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
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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.
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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:
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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.
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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.
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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
28

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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
32

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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.
Workshop  Summary
36

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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
38

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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
40

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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
42

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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
44

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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
                                        A-l

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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
A-2

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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
                                                                      B-l

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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
                                                                      B-2

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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
                                                                      B-3

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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
                                                                   B-4

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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
C-2

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