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Research

Research

Research

Website

https://sonet.ecoinformatics.org/front-page

Summary

Advances in 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. A recent NSF-funded workshop on multi-disciplinary data management concluded that interoperability can be significantly improved by better describing data at the level of observation and measurement, rather than the traditional focus at the level of the data set. That is, for systems to interoperate effectively, the scientific community must unify the various existing approaches for representing and describing observational data. A community-sanctioned, unified data model for observational data is thus needed to enable interoperability among existing data resources, which will in turn provide the necessary foundation to support cross-disciplinary synthetic research in the environmental sciences. The investigators propose the Scientific Observations Network to initiate a multi-disciplinary, community-driven effort to define and develop the necessary specifications and technologies to facilitate semantic interpretation and integration of observational data. The technological approaches will derive from recent advances in knowledge representation that have demonstrated practical utility in enhancing scientific communication and data interoperability within the genomics community. This effort will constitute a community of experts consisting of environmental science researchers, computer scientists, and information managers, to develop open-source, standards-based approaches to the semantic modeling of observational data. Subgroups of Network experts will also engage in extending this core data model to include a broad range of specific measurements collected by the representative set of disciplines, and a series of demonstration projects will illustrate the capabilities of the approaches to confederate data for reuse in broader and unanticipated contexts.

There is currently fragmentation among the environmental science subdisciplines, such that each is typically working to meet its own, internal data access and integration needs, without considering how data interoperability could be achieved more broadly through collaboration with researchers and technologists from other fields. By bringing together scientists from representative environmental disciplines, knowledge engineers and conceptual modeling experts, and specialist information managers working within these domains, we hope to initiate a new crosscutting network to derive consensus on technology strategies for achieving data interoperability. This will be accomplished by retaining the momentum of prior NSF-funded activities that have identified a clear path forward for dealing with data interoperability, recommending that the broader community develop and ratify a unified model for scientific observation onto which current and future data models can be superimposed. Key to the success of the proposed network will be outreach to the broader environmental science communities and stakeholders through a number of meetings and community-focused workshops. These activities will directly engage a diverse group of community members, allowing the broader community to contribute requirements and use cases, provide feedback on proposed approaches, and participate in community-building activities (such as ratification of a core data model). Education will also be key to project success and will be supported through a number of activities including student participation in network meetings and a workshop dedicated to training students, postdoctoral scientists, and researchers on the models and approaches developed through the network.

Funding

University of California-Santa Barbara (National Science Foundation funding)

Timeline

August 2008 — August 2009