Bidirectional Collaborative Frameworks for Decentralized Data Management

Along with the continuous evolution of data management systems for the new market requirements, we are moving from centralized systems towards decentralized systems, where data are maintained in different sites with autonomous storage and computation capabilities. There are two fundamental issues with such decentralized systems: local privacy and global consistency. By local privacy, the data owner wishes to control what information should be exposed and how it should be used or updated by other peers. By global consistency, the systems wish to have a globally consistent and integrated view of all data. In this paper, we report the progress of our BISCUITS (Bidirectional Information Systems for Collaborative, Updatable, Interoperable, and Trusted Sharing) project that attempts to systematically solve these two issues in distributed systems. We present a new bidirectional transformation-based approach to control and share distributed data, propose several distributed architectures for data integration via bidirectional updatable views, and demonstrate the applications of these architectures in ride-sharing alliances and gig job sites.