Commugrate -- A Community-based Data Integration System
This work is supported by the National Science Foundation under Grant No. IIS 0916614 and by the Cyber Center
PI: Prof. Mourad Ouzzani
CoPI: Prof. Ahmed Elmagarmid
Commugrate capitalizes on the information gained from the interactions of communities of humans with data sources. Commugrate tackles key challenges raised by the increase in the number of information sources used in science, engineering, and industry, as well as the need for large-scale data integration solutions to enable effective access to these sources. These challenges include schema matching and mapping, record-linkage, and data repair.
More specifically, Commugrate
- utilizes both direct and indirect contributions from different types of human communities with a focus on the latter contributions,
- solves key data integration issues using new evidences like usage and behavior data which have not been previously used,
- adopts a new technique for schema matching, which defines a new class of its own, namely usage-based schema matching,
- introduces the first of its genre technique for record linkage based on entities' behavior, and
- provides an adaptive feedback system to improve the quality of the data by making the best use of users feedback.