NSDI Cooperative Agreements Program
Agreement number 1434-HQ-97-AG-01867
Washington State Fish and Wildlife Geographic Data Clearinghouse
Washington Department of Fish and Wildlife
Prepared by James Eby and Christopher Ringo
The Washington Department of Fish and Wildlife (WDFW) is the lead agency responsible for the management of wildlife within the state of Washington.
WDFW collects and manages data on a wide range of wildlife species. These wildlife data have been a cornerstone in the identification of wildlife species at
risk, and in the Endangered Species Act (ESA) listing, management, and recovery processes in the past. These data have enabled WDFW, working with other
agencies, to achieve significant results in the wildlife conservation arena. In the role of lead wildlife data manager for Washington, WDFW receives many
requests for specific wildlife data. WDFW currently fields phone and surface mail inquiries for data availability and content in a manual, staff-intensive
process. A largely paper and surface mail driven system is then used to fill requests for data and maps.
The objectives of this project were to:
- Create metadata for key data sets to enable customers to easily determine data availability, geographic coverage, and characteristics.
- Place the metadata on a Clearinghouse node for internet search access.
- Provide direct access for users to download GIS data over the Internet.
A. Create Metadata
Our objective was to create metadata for some data holdings at WDFW and for the Washington GAP project data. We chose to create metadata for the
Department Priority Habitats and Species (PHS) data base. The PHS data describe the locations and needs of the species that WDFW considers to be the
highest priority for protection and management. These include listed species, and species of important recreational and commercial value in Washington. PHS
data are widely used by other governmental agencies for management and regulatory purposes. We also created metadata for the Washington GAP project data
(WAGAP). The WAGAP data represent a large body of biological data generated by the Washington project and contributed to the national USGS-sponsored
GAP biodiversity evaluation studies. WDFW has assumed the role of archiving and distributing the WAGAP data to interested parties.
B. Place the Metadata on a Clearinghouse Node
The purpose of creating the metadata was to make the data descriptions accessible to discovery through the Clearinghouse Internet search mechanism. At the
time this project was proposed, no Clearinghouse existed in Washington and the project considered creating and managing a new node. However, at about the
time this project got under way, a Clearinghouse node sponsored by the Washington Geographic Information Council (WAGIC) was implemented. Since
WDFW is a member organization of WAGIC, we decided to cooperate with the WAGIC Washington Geospatial Clearinghouse rather than create a parallel
capability. WDFW became a member of the WAGIC Clearinghouse steering committee, and installed the project metadata on that node.
C. Provide Direct Access for Users to Download Biological Data
In our initial project proposal, we anticipated user access to WDFW data continuing mostly through an off-line ordering process, with the possibility of
implementing a data server. However, since we did not need to put effort into creating and managing a clearinghouse node of our own, we directed more
energy and project resources into creating a direct access service for users to download biological data. We acquired hardware and developed a biological data
Internet site where users are directed via hypertext links from the metadata residing on the WAGIC Clearinghouse. The biological data server provides
additional information via HTML documents on World Wide Web pages (WWW), and includes GIS data sets available for downloading on an FTP server.
The WWW information can be directly browsed at http://wdfw.wa.gov/conservation/gap/.
In our proposal, we anticipated cooperative project activities with several other groups. In the case of metadata development for WAGAP data, we formed a
contractual relationship with the WAGAP group at the University of Washington. This relationship was very valuable in the metadata development for
WAGAP since the UW group were the creators of the data. As a result, we recommend that metadata are best developed by the creators or stewards of the
underlying GIS data sets.
We also have a strong relationship with WAGIC, the sponsors of the Washington Geospatial Clearinghouse. In Washington, the cooperative approach to
developing and managing a clearinghouse node has worked well, and has provided a better service to clearinghouse users through the presentation of multi-agency metadata on a single node.
We communicated with other interested groups regarding our project activities informally, and made three formal presentations. Two talks about our project
were given at meetings of the Washington Geographic Information Council. A presentation was also made at the national meeting of the American Congress
on Surveying and Mapping.
B. Technology and Software Tools
Our technology decisions were divided into two basic areas, the choice of metadata development tools, and the choice of a platform to host the WWW and FTP
services. We believe that technology chosen for any project should be solid state-of-the-art, avoid the "bleeding edge", be compatible with existing staff
capabilities, and be cost effective.
Our choice for a metadata creation tool was driven by the objective to incorporate the Content Standard for the National Biological Information Infrastructure
(NBII) profile extensions to the NSDI metadata standard. We chose the MetaMaker metadata tool developed by the USGS Biological Resources Division since
it included the NBII profile, and was compatible with our PC systems. We hoped that MetaMaker would be relatively user friendly, but encountered some
problems in sharing metadata files between users, as described in more detail later.
We chose Sun Microsystem equipment as the hardware platform to host the Internet services. Current staff have the expertise to manage and maintain Sun
equipment. Configuring the FTP server to meet our security requirements was the most difficult task. We over-built the server capacity to plan for future data
C. Metadata Standards
Our metadata efforts included writing descriptions for the WDFW PHS data and the Washington Gap project data. The most time-consuming portion of the
project was definitely the metadata creation. Our most difficult metadata undertaking was to write the descriptions for vertebrate distribution layers created by
the Washington Gap Analysis Project (WAGAP). As mentioned earlier, we were documenting biological data, so we decided to create the metadata with the
(NBII) Metadata extensions, and use the NBII's MetaMaker metadata entry tool.
In order to "get our feet wet", we decided to first create metadata for one of Agency's principal data sets, a polygon layer called Priority Habitats and Species
(PHS). The data structure of PHS is much less complex than that of the WAGAP data, having no related tables or ancillary data sets associated with it. This
allowed us to concentrate on learning the NBII Content Standard and MetaMaker. To kick off the effort, two analysts attended a metadata workshop sponsored
by Washington State's Geographic Information Council. In the workshop, we began the metadata entry for the PHS data set, and completed the entry afterward.
In all, this first entry took only about eight to ten hours of staff time, due mainly to the fact that most all of the information documenting the layer already
existed in other formats, and just needed to be rearranged and entered into MetaMaker.
After creating the PHS metadata entry, we turned our attention to the WAGAP data. The first major hurdle we had to overcome was to try to anticipate how the
WAGAP data were most likely going to be used, and then decide on the best data presentation format for those uses. Due to the rather complex data structures
and the relationships between the various data sets, this was not entirely straightforward. In addition, due to the sheer number of data sets (399 separate
vertebrate distribution coverages, plus the land cover), we needed to decide on how best to group the data sets in order to write the metadata. I.e., should we
create a separate metadata entry for each of the 399 vertebrate distributions, or could we logically group some of them together and write metadata for each
To give a better idea of the challenges we faced here, it would be helpful to first give a little detail on the content and structure of these data. The basic data set
of WAGAP is a land cover layer containing roughly 15,000 polygons. Each polygon is coded with particular habitat characteristics. The layer is a stand-alone
coverage, but also forms the basis for modeling the spatial distributions of the 399 bird, mammal, reptile and amphibian species included in the project (each
species distribution was modeled based on the habitat characteristics represented in the land cover polygons). Because of this, the "native" data presentation
format of each of the vertebrate distributions is a database table that relates to (and is therefore dependent on) the land cover layer. We realized that although
some users would be able to utilize this data structure, some would surely prefer a stand-alone coverage for each species distribution.
Our initial challenges in writing metadata for the WAGAP data then, were tackling the questions of how to (or whether to) group the data sets, and which data
presentation form the metadata would be written for. We decided that the clearest and most practical answer to the first question was to bend the "one data set,
one metadata entry" rule, and group the vertebrate distributions into three sets - reptiles and amphibians, birds, and mammals - and write one metadata entry for
each group. Since the background, lineage, and methodology for creating the vertebrate distributions was consistent within each group, it seemed much more
practical and useful to write one metadata entry for each group and list the individual species under the "taxonomic keywords" section, rather than creating a
separate entry for each individual species. To resolve the second question, we decided that it would be best to write a WWW interface for the data download
that would clearly explain the differences between the two data presentation forms for the vertebrate distributions, and keep the metadata entry general enough
to cover any presentation form (we also included graphics of each species distribution on the Web page). The URL for both the WWW interface and an FTP
interface are embedded in each metadata entry.
The first WAGAP data set for which we created metadata was the land cover layer. In all, this entry probably took two to three weeks of staff time to complete,
which included more time for gaining familiarity with the Content Standard and with MetaMaker. The first of the three vertebrate entries probably took a
similar amount of time, with a significant amount of the time being spent on the creation of species lists, and checking the species' scientific names for
compliance with the Integrated Taxonomic Information System (a requirement of the NBII standard). In both cases, some of the information could be pulled
from existing sources, but much of the detail of the processing steps, etc. had to be created from scratch. The second and third vertebrate entries went much
faster, taking perhaps a few days each.
Metadata training was not a difficult hurdle, since only a few staff were involved. Learning the metadata software only required the time to just sit down and do
it. The one area in the metadata standard that we found confusing was the difference between "processing steps" and "methodology steps". It took some time
to figure out where we should document the data creation steps.
One area in which we encountered some problems was with the use of MetaMaker. Specifically, we had two analysts working on the metadata in turns, having
to exchange the files back and forth. MetaMaker has an export/import capability, but we found it to be rather buggy. As a result, for the last metadata entry, we
edited the entry with a text editor and ran it through cns and mp by hand.
Out intention from the beginning was to use this project as a springboard to begin institutionalizing metadata creation and clearinghouse activities. We feel that
the project has accomplished that goal. We gained a better understanding of metadata creation which we intend to apply to other data management sectors. We
are committed to continued involvement in the management of the Washington Geospatial Data Clearinghouse. We also plan to expand the range of
geographic data offered for downloading on our WWW server, since we will benefit directly from staff workload efficiency.
The intent of this questionnaire is to gain an understanding of the impacts of your project effort, to examine the ingredients for sustaining project efforts, and to
assess the impact of the Cooperative Agreements Program itself. The questions can be completed by circling answers (on a 1 - 5 scale) and/or in some cases by
providing written responses.
Name: Jim Eby Phone Number: 360-902-2512
Project Title: Fish and Wildlife Data Clearinghouse
Fiscal Year of Award: FY97
A. PROJECT IMPACTS
1. Do you believe you achieved your project goals?
|No, definitely not
||Achieved some of the goals
||Achieved most of the goals
3. Of what value has your particular project effort been to you?
|Of little or no importance
||Below average importance
||Of moderate importance
||Above average importance
||Of very great importance
3.a. If you answered either 3, 4, or 5 please describe its importance:
The project helped start us on the road to metadata and clearinghouse activities. The ultimate judgement of the importance will be seen in how well we follow
through in the coming years.
4. Has this project made geospatial data more affordable or accessible than before?
|No, definitely not
||Difficult to tell
4.a. If possible, quantify (or describe) this change, ex. increase in # of users or % increase in sales, etc.?
Making data available for direct downlead has the potential to decrease staff work loads. In the first month of operation, the FTP biological data server
recorded over 150 hits. These represent potential staff saving in direct customer contact and data dissemination effort.
5. How has this project affected the targeted end users for whom you developed your data service? (i.e., What difference did it make for them?)
The Clearinghouse effort had enhanced the ability of users to discover the existence of data, and the data server has made it easier and faster for users to obtain
data sets in a digital format.
6. Will you continue to implement the NSDI? Yes (or No)
6.a. If yes, please describe in general terms, the essence of these implementation activities.
We intend to extend formal metadata to other agency data holdings, and to include metadata development in new data creation efforts. We will expand the
range of data available for direct download over the Internet. We are also committed to involvement in Framework data development.
6.b. Has the project effort and/or tenets of the NSDI been institutionalized within the other organizations involved in the project?
|Only very little
7. Have you had inquiries from other organizations about your project?
|Very seldom or never
7.a. Are you aware of other organizations that have initiated similar efforts as a result of your project work? (Yes or) No
8. What are three observable, measurable benefits of your project to date (ex., improved data management, improved understanding /interest in metadata
creation by state and university community, recognition as a central facility for data distribution)?
A. Improved commitment to metadata creation
B. Improved accessability to data
C. Better coordination among agencies in clearinghouse activities.
8.a. The benefits you've experienced have been:
|Much less than expected
||Less than expected
||Pretty much as expected
||More than expected
||Much more than expected
9. Describe how you've disseminated information about your project. What have been the most effective ways of achieving public awareness of your project?
We have made several presentations on our project activities including two talks at meetings of the Washington Geographic Information Council, and one
presentation at the national meeting of the American Congress on Surveying and Mapping. We also have direct links to WWW project information from our
official agency home page.
10. Did the results and experiences from other NSDI Competitive Cooperative Agreements Program projects help your effort?
|Did not contribute at all
||Contributed a little
||Contributed a great deal
B. SUSTAINING YOUR PROJECT
1. What are the sustainable results of your project (ex., creation of an operational C-2 level clearinghouse, development of agency metadata records)?
Created metadata, participated in clearinghouse management, and created of an operational data serving capability. The project resulted in an operational C-3
level clearinghouse for the project data.
2. How are the objectives of your project likely to be sustained, and where do you expect to find follow-on funding for it?
We plan to continue the management of the data server with normal state operating funds. We hope to continue creating metadata by making an institutional
commitment to metadata as a part of normal project activity.
3. What recommendations regarding sustainability do you have for other groups? (This could be in the context of funding, program development, and/or
The key to sustaining activities will be that organizations recognize that the activities are part of their normal business requirements, and not a peripheral
activity that requires extra funding.
4. Will the partnerships you've established be continued after the project's completion?
|No, definitely not
||Yes, with some of the partners
||Yes, with most of the partners
5. What do you predict will be the three long-range most important observable, measurable contributions of your project?
Proportion of data sets with metadata entries, number of data sets available for download, and number of customers utilizing the data resources.
C. COOPERATIVE AGREEMENTS PROGRAM IMPACTS
1. Were you aware of the NSDI before participating in this Cooperative Agreements Program?
|No, definitely not
||Only very little
||Very much so
1.a. Was the Program instrumental in making you more fully aware of the NSDI?
Yes (or No)
2. Did the NSDI Cooperative Agreements Program help further your program efforts?
|Only very little
2.a. Please describe how this NSDI Cooperative Program helped further your efforts?
The project funding allowed us to learn how to implement clearinghouse and metadata activities and gave us the startup funding to implement the data serving
capability. With those things accomplished, we are in a strong position to continue the activity.
3. Without the FGDC investment would you have undertaken your project?
||Yes, doing so already
||Yes, but 1 year later
||Yes, but 2 years later
||Yes , but much (>2 yrs) later
4. Did this Cooperative Agreements Program help you promote the NSDI tenets to others? Did it strengthen your ability to promote the NSDI to
||Very much so
5. What else should we examine when evaluating the NSDI Competitive Cooperative Agreements Program?
6. What could the FGDC have done to help you be more successful?
Better definition of metadata elements.
Improved metadata tool training, or development of tutorials.