Abstract
We introduce the BioFuice approach for integrating data from different private and public data sources and ontologies. BioFuice follows a peer-to-peer-like data integration based on bidirectional mappings. Sources and mappings are associated with a domain model to support a semantically meaningful interoperability. BioFuice extends the generic iFuice integration platform which utilizes specific operators for data fusion and workflow-like script programs. BioFuice supports explorative data analysis and query and search capabilities. We outline the integration approach by an illustrating scenario, the architecture of BioFuice and its query interface.
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Kirsten, T., Rahm, E. (2006). BioFuice: Mapping-Based Data Integration in Bioinformatics. In: Leser, U., Naumann, F., Eckman, B. (eds) Data Integration in the Life Sciences. DILS 2006. Lecture Notes in Computer Science(), vol 4075. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11799511_12
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DOI: https://doi.org/10.1007/11799511_12
Publisher Name: Springer, Berlin, Heidelberg
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