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Personal data provides important business value, for example, in the personalization of services. In addition, companies are now moving toward new business models, in which products and services are offered without charge in exchange for targeted advertising revenue. New privacy regulations are increasingly requiring organizations to explicitly state their data practices in privacy policies, including which data types will be collected. By consenting to data collections described in a policy, the user acknowledges that he or she is granting the company the authorizations needed to access their data. When data practices change, a new version of the policy is released. This release can occur a few times year, when requirements are rapidly changing for the collection and processing of personal data. Furthermore, the user may change his or her privacy consent by opting in or out of the policy. We propose a formal framework to support companies and users in their understanding of policies evolution under consent regime that supports both retroactive and non-retroactive consent and consent revocation. Preliminary results include an ontology for policy evolution, expressed in Description Logic, that can be used to formalize consent and data collection logs and then query for which data types can be legally accessed. Travis D. Breaux is an Associate Professor of Computer Science, appointed to the School of Computer Science at Carnegie Mellon University. He is Director of CMU’s Requirements Engineering Lab, which collaborates with affiliate researchers, worldwide, and Director of the Masters of Software Engineering Professional Programs. He holds the Ph.D. in Computer Science from North Carolina State University, the B.S. in Computer and Information Science from the University of Oregon and the B.A. in Anthropology from the University of Houston. Dr. Breaux's research program investigates new methods and tools for developing correct secure and trustworthy software. Dr. Breaux received a 2015 NSF CAREER award and his research has been recognized by an honorable mention for most influential paper award and best paper awards and nominations from the IEEE International Requirements Engineering Conference.
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