H.V. Jagadish of the University of Michigan in the U.S. will take disparate datasets on diverse topics, including education, health, and the environment, which are often reported using different geographical units such as Zip Code or County, and realign them to a common unit so they can be better compared and used. Jagadish will develop four general techniques for aligning data partitions and apply them to existing datasets in one state in the U.S. so that they can be viewed according to different geographical units. Jagadish will also produce an interface so that policy analysts and NGOs can easily access and query these data, and collect feedback to improve the approach.
More information about Increasing Interoperability of Social Good Data (Round 11)