Abstract
Similar to content on the web, scientific data is highly heterogeneous and can benefit from rich semantic descriptions. We are particularly interested in developing an infrastructure for expressing explicit semantic descriptions of ecological data (and life-sciences data in general), and exploiting these descriptions to provide support for automated data integration and transformation within scientific workflows [2]. Using semantic descriptions, our goal is to provide scientists with: (1) tools to easily search for and retrieve datasets relevant to their study (i.e., data procurement), (2) the ability to select a subset of returned datasets as input to a scientific workflow, and (3) automated integration and restructuring of the selected datasets for seamless workflow execution.
This work supported in part by NSF grant ITR 0225674 (SEEK).
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Bowers, S., Thau, D., Williams, R., Ludäscher, B. (2005). Data Procurement for Enabling Scientific Workflows: On Exploring Inter-ant Parasitism. In: Bussler, C., Tannen, V., Fundulaki, I. (eds) Semantic Web and Databases. SWDB 2004. Lecture Notes in Computer Science, vol 3372. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31839-2_5
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