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Preserving privacy in shared provenance data

Lookup NU author(s): Professor Paolo MissierORCiD, Dr Jeremy Bryans

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This is the final published version of a report that has been published in its final definitive form by Newcastle University, 2013.

For re-use rights please refer to the publisher's terms and conditions.

Abstract

Provenance management still lacks robust models for shar- ing provenance data between multiple parties while keeping parts of it private to the owner. This limits the potential for provenance dissemination, which is a critical step in enabling data sharing amongst partners with limited a priori mutual trust. In turn, this has a negative impact on data-intensive science and its associated research publication repositories, on audit tasks, as well as on increasingly common collabora- tive dynamic coalitions scenarios. We propose a method for preserving privacy by creating abstractions over provenance graphs, we apply it to provenance sharing, and illustrate it on a health care case study.

Publication metadata

Author(s): Missier P, Bryans J, Danger R, Curcin V

Publication type: Report

Publication status: Published

Series Title: School of Computing Science Technical Report Series

Year: 2013

Pages: 15

Print publication date: 01/01/2013

Source Publication Date: January 2013

Report Number: 1366

Institution: Newcastle University

Place Published: Newcastle upon Tyne

URL: http://www.cs.ncl.ac.uk/publications/trs/papers/1366.pdf

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