HR: 10:44h
AN: IN52A-03    [Abstracts]
TI: Community-Driven Initiatives to Achieve Interoperability for Ecological and Environmental Data
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: Bowers, S
EM: sbowers@ucdavis.edu
AF: Genome Center, University of California, Davis, CA 95616, 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
AB: Advances in ecology and environmental science increasingly depend on information from multiple disciplines to tackle broader and more complex questions about the natural world. Such advances, however, are hindered by data heterogeneity, which impedes the ability of researchers to discover, interpret, and integrate relevant data that have been collected by others. Here, we outline two community-building initiatives for improving data interoperability in the ecological and environmental sciences, one that is well-established (the Ecological Metadata Language [EML]), and another that is actively underway (a unified model for observations and measurements). EML is a metadata specification developed for the ecology discipline, and is based on prior work done by the Ecological Society of America and associated efforts to ensure a modular and extensible framework to document ecological data. EML "modules" are designed to describe one logical part of the total metadata that should be included with any ecological dataset. EML was developed through a series of working meetings, ongoing discussion forums and email lists, with participation from a broad range of ecological and environmental scientists, as well as computer scientists and software developers. Where possible, EML adopted syntax from the other metadata standards for other disciplines (e.g., Dublin Core, Content Standard for Digital Geospatial Metadata, and more). Although EML has not yet been ratified through a standards body, it has become the de facto metadata standard for a large range of ecological data management projects, including for the Long Term Ecological Research Network, the National Center for Ecological Analysis and Synthesis, and the Ecological Society of America. The second community-building initiative is based on work through the Scientific Environment for Ecological Knowledge (SEEK) as well as a recent workshop on multi-disciplinary data management. This initiative aims at improving interoperability by describing the semantics of data at the level of observation and measurement (rather than the traditional focus at the level of the data set) and will define the necessary specifications and technologies to facilitate semantic interpretation and integration of observational data for the environmental sciences. As such, this initiative will focus on unifying the various existing approaches for representing and describing observation data (e.g., SEEK's Observation Ontology, CUAHSI's Observation Data Model, NatureServe's Observation Data Standard, to name a few). Products of this initiative will be compatible with existing standards and build upon recent advances in knowledge representation (e.g., W3C's recommended Web Ontology Language, OWL) that have demonstrated practical utility in enhancing scientific communication and data interoperability in other communities (e.g., the genomics community). A community-sanctioned, extensible, and unified model for observational data will support metadata standards such as EML while reducing the "babel" of scientific dialects that currently impede effective data integration, which will in turn provide a strong foundation for enabling cross-disciplinary synthetic research in the ecological and environmental sciences.
DE: 0430 Computational methods and data processing
DE: 0434 Data sets
SC: Earth and Space Science Informatics [IN]
MN: 2007 Fall Meeting