Publications

Privacy enforcement in data analysis workflows

Abstract

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.

Date
March 14, 2026
Authors
Yolanda Gil, William K Cheung, Varun Ratnakar, Kai-kin Chan
Journal
Privacy Enforcement and Accountability with Semantics (PEAS2007)
Pages
46