HR: 08:17h
AN: IN51C-02 INVITED    [Abstracts]
TI: Towards a core ontology for integrating ecological and environmental ontologies to enable improved data interoperability
AU: * Bowers, S
EM: sbowers@ucdavis.edu
AF: Genome Center, University of California, Davis, CA 95616, United States
AU: Madin, J
EM: madin@nceas.ucsb.edu
AF: National Center for Ecological Analysis and Synthesis, University of California, Santa Barbara, CA 93101, United States
AU: Jones, M
EM: jones@nceas.ucsb.edu
AF: National Center for Ecological Analysis and Synthesis, University of California, Santa Barbara, CA 93101, United States
AU: Schildhauer, M
EM: schild@nceas.ucsb.edu
AF: National Center for Ecological Analysis and Synthesis, University of California, Santa Barbara, CA 93101, United States
AU: Ludaescher, B
EM: ludaesch@ucdavis.edu
AF: Genome Center, University of California, Davis, CA 95616, United States
AB: Research in the ecological and environmental sciences increasingly relies on the integration of traditionally small, focused studies to form larger datasets for synthetic analyses. However, a broad range of data types, structures, and semantic subtleties occur in ecological data, making data discovery and integration a difficult and time-consuming task. Our work focuses on capturing the subtleties of scientific data through semantic annotations, which involve linking ecological data to concepts and relationships in domain-specific ontologies, thereby enabling more advanced forms of data discovery and integration. A variety of ontologies related to ecological data are actively being developed, ranging from low-level and highly focused vocabularies to high-level models and classifications. However, as the number of ontologies and their included terms increase, organizing these into a coherent framework useful for data annotation becomes increasingly complex (we note that similar issues have been recognized within the molecular biology and bioinformatics communities). We describe a core ontology model for semantic annotation that provides a structured approach for integrating the growing number of ecology-relevant ontologies. The ontology defines the notion of "scientific observation" as a unifying concept for capturing the basic semantics of ecological data. Observations are distinguished at the level of the entity (e.g., location, time, thing, concept), and characteristics of an entity (e.g., height, name, color) are measured (named or classified) as data. The ontology permits observations to be related via context (such as spatial or temporal containment), further supporting the discovery and automated comparison and alignment (e.g., merging) of heterogeneous data. The core ontology also defines a set of extension points that can be used to either directly build new domain ontologies (as extension ontologies), or to provide a common basis to which existing ontologies can be mapped. Thus, by enforcing a well-defined and high-level structure, the core ontology helps organize and integrate the growing number of ontologies, leading to better data discovery and integration techniques for semantically annotated data.
DE: 0430 Computational methods and data processing
DE: 0434 Data sets
SC: Earth and Space Science Informatics [IN]
MN: 2007 Fall Meeting