Data Coordination: Supporting Contingent Updates

In many scenarios, a contingent data source may benefit by coordinating with external heterogeneous sources upon which it depends. The administrator of this contingent source needs to update it when changes are made to the external base sources. For example, when a building design is updated, the contractor’s cost estimate must be updated, too. The goal of data coordination is to update a contingent source, C, based on changes to an independently maintained base source, B. This paper introduces a data coordination system which allows C to coordinate its data without imposing significant requirements on B. Our system uses declarative mappings between B and C and performs coordination in two stages View Differencing — finding changes to an intermediate view of B based on its mapping to C, and Update Translation — translating the view differencing result into updates on C. We present and evaluate novel solutions to both stages and demonstrate their feasibility on real world problems.