Privacy has become increasingly important to the database community, which is reflected by a noteworthy increase in research papers appearing in the literature. While researchers often assume that all readers universally hold their definition of "privacy", this is rarely the case; so many papers addressing key challenges in this domain have actually produced results that do not consider the same problem, even when using similar vocabularies. This talk will provide an explicit definition of data privacy suitable for ongoing work in data repositories such as a DBMS or for data mining. The talk will provide the larger context for the way privacy is defined legally and legislatively in various jurisdictions but primarily provides a taxonomy capable of thinking of data privacy technologically. We then demonstrate the taxonomy's utility by illustrating how this perspective makes it possible to understand the important contribution made by researchers to the issue of privacy. The talk will also argue that effective privacy management must make privacy a first order principle of data management and transmission.
Ken Barker is a Professor of Computer Science and Head of the Department at the University of Calgary (on sabbatical) with particular expertise in the area of database management systems. He holds a Ph.D. in Computing Science from the University of Alberta (1990) and has 25 years of experience working with industrial computer systems and in research. Dr. Barker has published extensively in areas as diverse as distributed systems, software engineering, transaction systems, simulations and security. His current interests include developing data repository systems that provide privacy protection for data suppliers while allowing collectors to utilize the data within the guidelines explicitly agreed to by the provider at the time it was acquired. The research objectives include developing a privacy preserving database system and privacy preserving data mining strategies.