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NSF Observations Workshop 2007


Broad-scale ecological studies often require information assembled from multiple disciplines including biology (e.g., genetics, physiology, and paleontology), the physical sciences (e.g., geography, meteorology, and hydrology), and increasingly the social sciences (e.g., economics and sociology). In such studies, data heterogeneity creates major informatics challenges that include the need to better discover, access, interpret, and integrate relevant data that have been collected by others. Despite the advances made using metadata and community-wide data networks, science needs robust, open, and generic software systems that address the semantic ambiguities of heterogeneous data. New strategies for managing observational data are needed so that systems can better interpret the semantics of observations to resolve issues impeding synthesis. For these systems to interoperate effectively, however, the scientific community must first unify the various existing approaches for representing observational data. A community-sanctioned data model for ecological and environmental observational data will provide an important mechanism for informatics efforts to enable interoperability among existing data resources, ultimately leading to more improved, comprehensive, cross-disciplinary synthetic research.

Workshop Objectives

The objectives of this workshop will be to discuss and define the features and requirements for a unified data model of observational data that can be shared across ecological and environmental sciences, and to clarify the infrastructure necessary for the scientific community to develop, maintain, and support such a model. The objectives for this proposed workshop constitute five distinct tasks: (1) define “observational data”; (2) specify the capabilities enabled by a shared model for observational data; (3) critically review existing models for observational data, in light of earlier points above, and clarify the advantages and challenges of creating a shared framework for capturing observational data; (4) enumerate specific requirements for a shared model for observational data; and (5) discuss the issues associated with creating and maintaining a shared model for observational data with a community-wide, open-participation effort.

General Information


Name InstitutionBreakout Group
Allen, PaulCornell Lab of Ornithology, Cornell University1
Barker, KristinConservation Systems Division, NatureServe2
Lin, KaiSan Diego Supercomputer Center, University of California, San Diego 1
Benson, BarbaraGlobal Lake Ecological Observatory Network4
Bermudez, LuisMonterey Bay Aquarium Research Institute2
Blum, StanleyCalifornia Academy of Sciences2
Bowers, ShawnUC Davis Genome Center2
Chiu, KennethComputer Sciences, State University of New York4
Zeman, LeeEvergreen State College 4
Horsburgh, JeffEnvironmental Management Research Group, Utah Water Research Laboratory3
Jax, KurtDepartment of Conservation Biology, Helmholtz Centre for Environmental Research1
Jones, MatthewNational Center for Ecological Analysis and Synthesis4
Kelling, SteveCornell Lab of Ornithology, Cornell University3
Kennedy, JessieSchool of Computing, Napier University1
Liu, XianhuaNational Evolutionary Synthesis Center, Duke University3
Madin, JoshuaNational Center for Ecological Analysis and Synthesis1
McCartney, PeterBiological Databases and Informatics, National Science Foundation-
McGuinness, DeborahKnowledge Systems Laboratory, Stanford University2
Mirtl, MichaelFederal Environment Agency, Austria3
Morris, RobertCollege of Science and Mathematics, University of Massachusetts Boston4
Parr, CynthiaUniversity of Maryland Institute for Advanced Computer Studies3
Piasecki, MichaelDepartment of Civil & Architectural Engineering, Drexel University
Raskin, RobertNASA Jet Propulsion Laboratory, California Institute of Technology1
Schildhauer, MarkNational Center for Ecological Analysis and Synthesis3
Servilla, MarkLTER Network Office, University of New Mexico2
Stein, BruceConservation Science Division, NatureServe4

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