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- Title
A knowledge environment for the biodiversity and ecological sciences.
- Authors
Michener, William K.; Beach, James H.; Jones, Matthew B.; Ludäscher, Bertram; Pennington, Deana D.; Pereira, Ricardo S.; Rajasekar, Arcot; Schildhauer, Mark
- Abstract
The Science Environment for Ecological Knowledge (SEEK) is a knowledge environment that is being developed to address many of the current challenges associated with data accessibility and integration in the biodiversity and ecological sciences. The SEEK information technology infrastructure encompasses three integrated systems: (1) EcoGrid—an open architecture for data access; (2) a Semantic Mediation System based on domain-specific ontologies; and (3) an Analysis and Modeling System that supports semantically integrated analytical workflows. Multidisciplinary scientists and programmers from multiple institutions comprise the core development team. SEEK design and development are informed by three multidisciplinary teams of scientists organized in Working Groups. The Biodiversity and Ecological Analysis and Modeling Working Group informs development through evaluation of SEEK efficacy in addressing biodiversity and ecological questions. The Knowledge Representation Working Group provides knowledge representation requirements from the domain sciences and develops the corresponding knowledge representations (ontologies) to support the assembly of analytical workflows in the Analysis and Modeling System, and the intelligent data and service discovery in the EcoGrid. A Biological Classification and Nomenclature Working Group investigates solutions to mediating among multiple taxonomies for naming organisms. A multifaceted education, outreach and training program ensures that the SEEK research products, software, and information technology infrastructure optimally benefit the target communities.
- Subjects
SEEK (Computer system); BIOLOGY; INFORMATION storage &; retrieval systems; BIODIVERSITY; ECOLOGY; COMPUTERS in systems design; COMPUTERS in biology; EXPERT systems; KNOWLEDGE representation (Information theory); ARTIFICIAL intelligence
- Publication
Journal of Intelligent Information Systems, 2007, Vol 29, Issue 1, p111
- ISSN
0925-9902
- Publication type
Article
- DOI
10.1007/s10844-006-0034-8