Thuraisingham, Bhavani M.Kantarcioglu, MuratBertino, E.Bakdash, Jonathan Z.Fernandez, M.2019-09-272019-09-272018-06-139781450356664https://hdl.handle.net/10735.1/6925Full text access from Treasures at UT Dallas is restricted to current UTD affiliates (use the provided Link to Article).Massive amounts of data are being collected, stored, and analyzed for various business and marketing purposes. While such data analysis is critical for many applications, it could also violate the privacy of individuals. This paper describes the issues involved in designing a privacy aware data management framework for collecting, storing, and analyzing the data. We also discuss behavioral aspects of data sharing as well as aspects of a formal framework based on rewriting rules that encompasses the privacy aware data management framework. ©2018 Association for Computing Machinery.en©2018 Association for Computing MachineryData protectionPrivacy, Right ofData--Access controlarticleThuraisingham, B., M. Kantarcioglu, E. Bertino, J. Z. Bakdash, et al. 2018. "Towards a privacy-aware quantified self data management framework." Proceedings of the 23nd ACM on Symposium on Access Control Models and Technologies: 173-184, doi: 10.1145/3205977.3205997