Privacy enforcement in data analysis workflows

Yolanda Gil, William Kwok Wai Cheung, Varun Ratnakar, Kai Kin Chan

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

6 Citations (Scopus)


Collaborative e-Science projects commonly require data analysis to be performed on distributed data sets which may contain sensitive information. In addition to the credential-based privacy protection, ensuring proper handling of computerized data for disclosure and analysis is particularly essential in e-Science. In this paper, we propose a semantic approach for enforcing it through workflow systems. We define privacy preservation and analysis-relevant terms as ontologies and incorporate them into a proposed policy framework to represent and enforce the policies. We believe that workflow systems with the proposed privacy-awareness incorporated could ease the scientists in setting up privacy polices that suit for different types of collaborative research projects and can help them in safeguarding the privacy of sensitive data throughout the data analysis lifecycle.

Original languageEnglish
Title of host publicationProceedings of the ISWC'07 Workshop on Privacy Enforcement and Accountability with Semantics (PEAS'07)
EditorsTim Finin, Lalana Kagal, Daniel Olmedilla
Number of pages8
Publication statusPublished - Nov 2007
EventISWC 2007 Workshop on Privacy Enforcement and Accountability with Semantics, PEAS 2007 - Busan, Korea, Republic of
Duration: 12 Nov 200712 Nov 2007

Publication series

NameCEUR Workshop Proceedings
ISSN (Print)1613-0073


ConferenceISWC 2007 Workshop on Privacy Enforcement and Accountability with Semantics, PEAS 2007
Country/TerritoryKorea, Republic of
Internet address

Scopus Subject Areas

  • Computer Science(all)

User-Defined Keywords

  • Privacy
  • Scientific workflows
  • Trust
  • Workflow generation


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