Department of Computer Science
Privacy enforcement in data analysis workflows
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 eScience. 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.
Workflow generation, scientific workflows, privacy, trust
Source Publication Title
Proceedings of the ISWC'07 Workshop on Privacy Enforcement and Accountability with Semantics (PEAS'07)
Finin, Tim ; Kagal, Lalana ; Olmedilla, Daniel
© 2007 for the individual papers by the papers' authors. Copying permitted for private and academic purposes. Re-publication of material from this volume requires permission by the copyright owners.
This research was supported in part by the Air Force Office of Scientific Research (AFOSR) through grant FA9550-06-1-0031.
Link to Publisher's Edition
Gil, Yolanda, William K. Cheung, Varun Ratnakar, and Kai-kin Chan. "Privacy enforcement in data analysis workflows." Proceedings of the ISWC'07 Workshop on Privacy Enforcement and Accountability with Semantics (PEAS'07) (2007): 46-53.