Privacy Preserving Data Integration and Sharing Chris Clifton, AnHai Doan, Ahmed K. Elmagarmid, Murat Kantarcioglu, Gunther Schadow, Dan Suciu, and Jaideep Vaidya   View Paper (PDF)   Return to Session 1 Abstract Integrating data from multiple sources has been a longstanding challenge in the database community. Techniques such as privacy-preserving data mining promises privacy, but assume data has integration has been accomplished. Data integration methods are seriously hampered by inability to share the data to be integrated. This paper lays out a privacy framework for data integration. Challenges for data integration in the context of this framework are discussed, in the context of existing accomplishments in data integration. Many of these challenges are opportunities for the data mining community. ©2005 Association for Computing Machinery