Integrating and sharing data from multiple sources has been a long-standing challenge in the database community. This problem is crucial in numerous contexts, including data integration for enterprises and organizations, data sharing on the Internet, collaboration among government agencies, and the exchange of scientific data. Many applications of national importance, such as emergency preparedness and response; as well as research in many scientific domains, require integrating and sharing data among participants.
Data integration is seriously hampered by an inability to ensure privacy. Without a privacy framework, sources are reluctant to share their data. Problems include fear of disclosing confidential information as well as regulations protecting individual privacy. While there has been progress in computing aggregations of distributed data without disclosing that data; e.g., privacy-preserving distributed data mining, it assumes data integration problems (schema matching, record linkage) are solved. As a consequence, the lack of a privacy-preserving data integration framework has become a key bottleneck to deploying data integration.
This project will develop the technology needed to create and manage federated databases while controlling the disclosure of private data. While the emphasis will be on general techniques for data integration that preserve privacy, the project will work in the context of diverse but particularly relevant problem domains, including scientific research and emergency preparedness. Involvement of domain experts from these fields in developing and testing the techniques will ensure impact on areas of national importance.
