Geospatially Enabled Environmental Databases Rocket City Geospatial Conference November

2 Geospatially Enabled Databases  Enterprise decision support applications require access to diverse data in addition to traditional GIS layers  Geodatabase architectures greatly expand ability store and access diverse data  Such data is often in form of published reports, historical studies, imagery, etc.  Capitalizing on this type of data requires it to be “geospatially enabled” Transition from “maps” to “geospatial decision tools” Geodatabase allows a more conventional approach to data storage Data in flat file format presents additional challenges Geographic extents must be assigned to individual resource documents

3 Recent Examples of Such Projects  US Corps of Engineers Wolf Creek Dam Analysis  Spatially enabled over 60 years of data, CADD drawings, images, boring logs, spreadsheets, and photos  US Army National Guard Environmental Databases  Spatially enabled environmental databases for public involvement and environmental management

4 Department of Interior Ecospatial Information Database (ESID)  Department of Interior Minerals Management Service manages leasing in the Outer Continental Shelf  Non-renewable (oil and gas)  Renewable (wind, wave, current) energy sources  ESID Project goals  Support ecosystem-based management of activities permitted by MMS in the MMS Atlantic Planning Areas.  Compile georeferenced ecological information resources and associated metadata into a searchable geospatial database.  Provide compatible data for the MMS Multipurpose Marine Cadastre (MMC) system.

5 Project Concept  Collect all relevant data for the Atlantic MMS planning areas  Spatially enable relevant resources  Use areas of interest as basis for spatial query to identify relevant resources  Provide for data query of resources within areas of interest

6 Resource Data Collection  Assimilation of ecological data relative to the three MMS Atlantic Planning Areas of interest together with the scientific analysis required to determine what data is applicable to the program objectives.  Data might be 40+ years old  Relevance determines if it will be included

7 Resource Categories  Geology (including seafloor features, sediments)  Meteorology/climate  Air quality  Water quality (including contaminants)  Acoustic environment/underwater noise  Pelagic ecology (plankton, nekton, Sargassum, etc.)  Benthic ecology  Seafloor features  Infauna, meiofauna  Demersal fishes  Corals and hard/live bottom communities  Seagrass beds (state waters)  Incidental topics (included but not the focus of this study)  Marine mammals  Sea turtles  Marine and coastal birds

8 Resource Data Collection (Continued)  Searching for studies, surveys, scientific review papers, mapping efforts, GIS datasets, etc.  Preliminary search of bibliographic and library resources (e.g., Dialog ®, OCLC TM WorldCat, govt. libraries, etc.) to identify titles of potential interest  Output will determine whether search criteria must be refined Search Criteria (Keywords) Bibliographic/ Library Resource Preliminary Output Refined Keywords (as necessary) Full Resource Search

9 Resource Data Collection (Continued)  Search output will be analyzed by ISRT for relevance using a decision matrix  Develop a Preliminary Resource List which MMS will review and approve  Geographic information will be obtained for data as it is collected, where possible Internal Science Review Team Decision Matrix Preliminary Resource List Search Output

10 Resource Annotation and Geographic Characterization  Collected resources will be assigned geospatial data definitions describing geographic location within the three MMS Planning Areas  Applying spatial definitions of resources will allow spatial query within Areas of Interest for data extraction Geographic Characterization of Resources Spatial location is available within resource Assign geographic coordinates Authors and/or collaborators are Contacted Spatial location is not available within resource

11 Resource Data Extraction Within Areas of Interest  Relevant data/information pertinent to the needs of potential offshore leases will be extracted from resources within the ESID.  Draft Proposed OCS Oil and Gas Leasing Program ( )  The potential Virginia Lease Sale 220  The Data Extraction Team (DET) with expertise within each scientific area will facilitate data extraction for all applicable fields of study  Benthic Ecology  Ichthyology  Marine Botany  Water Quality  Toxicology  Geology

12 Resource Data Extraction Within Areas of Interest (Continued) Spatial extent of Areas of Interest defined and approved Spatial query of collected resources Data/information extracted by DET Data/information Loaded to ESID

13 Metadata  Will be created for spatially- enabled database  Geospatial resources will be associated with FGDC standards  Support transition to ISO standard  Perform evaluation of available metadata parsers (e.g.,mp)  Produce in XML  Perform QA

14 Metadata (Continued) Federal Geographic Data CommitteeFederal Geographic Data Committee's "Content Standard for Digital Geospatial Metadata" Version (FGDC-STD-001 June 1998)  General Categories: --Resource Info --Geospatial & Accuracy --Physical --Intellectual property

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16 ESID and Application Development  Designing the ecospatial database architecture, which includes: creating the database, populating the database with properly formatted data, and creating useful applications that allow the data to be fully utilized for the MMS management task.

17 ESID Database and Interface Development  ESID Design / Creation  ESID Population  Create Custom Map Interface

18 Arc Marine Data Model  Collaboration involving researchers from Oregon State University, Duke, NOAA, and The Danish Hydraulic Institute  ArcMarine model is a geodatabase template that provides a starting point for the conceptual design of the ocean features with spatial and temporal perspectives  Integrates natural and manmade features of the ocean realm  Provides a design approach to a volumetric model to represent the multidimensional and dynamic nature of ocean data and processes

19 Identify Potential Multi-Purpose Cadastre Data Sources  Potential MMC data sources will be identified and presented to the COTR for approval  Initial stages of the resource data collection will tentatively identify relevant data sources  Final identification of potential MMC data sources will be identified after ESID population and be easily retrieved by key word search  MMC data structure is currently under investigation with NOAA to ensure content requirements

20 Questions

21 Contacts DOI/MMS Program Manager- Mr. James Sinclair, (504) , AMEC Technical Project Manager- Mr. Brett Fritze, (615) , AMEC Program Manager- Mr. Lonnie Hearne, (615) ,