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DILS
2004
Springer

An Ontology-Driven Framework for Data Transformation in Scientific Workflows

9 years 11 months ago
An Ontology-Driven Framework for Data Transformation in Scientific Workflows
Abstract. Ecologists spend considerable effort integrating heterogeneous data for statistical analyses and simulations, for example, to run and test predictive models. Our research is focused on reducing this effort by providing data integration and transformation tools, allowing researchers to focus on "real science," that is, discovering new knowledge through analysis and modeling. This paper defines a generic framework for transforming heterogeneous data within scientific workflows. Our approach relies on a formalized ontology, which serves as a simple, unstructured global schema. In the framework, inputs and outputs of services within scientific workflows can have structural types and separate semantic types (expressions of the target ontology). In addition, a registration mapping can be defined to relate input and output structural types to their corresponding semantic types. Using registration mappings, appropriate data transformations can then be generated for each des...
Shawn Bowers, Bertram Ludäscher
Added 20 Aug 2010
Updated 20 Aug 2010
Type Conference
Year 2004
Where DILS
Authors Shawn Bowers, Bertram Ludäscher
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