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Overview:

This paper presents the design of a new middleware which provides support for trust and accountability in distributed data sharing communities. One application is in the context of scientific collaborations. Multiple researchers share individually collected data, who in turn create new data sets by performing transformations on existing shared data sets. In data sharing communities building trust for the data obtained from others is crucial. However, the field of data provenance does not consider malicious or untrustworthy users. By adding accountability to the provenance of each data set, this middleware ensures data integrity insofar as any errors can be identified and corrected.

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Format:PDFSize:126 KB
Date:Jan 2008
Pages:15

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