Abstract: Schema mappings are high-level specifications that describe the relationship between two database schemas. Schema mappings have been explored in depth during the past fifteen years and have turned out to be the essential building blocks in data exchange and data integration. Since in real-life applications schema mappings can be quite complex, it is important to develop methods and tools for deriving and explaining schema mappings. A promising approach to this effect is to use “good” data examples that illustrate the schema mapping at hand.

In this talk, we will present an overview of a body of work on characterizing and deriving schema mappings via a finite set of data examples, including characterizations of schema mappings via a finite set of universal examples and the learnability of schema mappings from data examples. The main emphasis will be on schema mappings specified by global-as-view constraints, that is, constraints specified by Horn formulas.

Short Bio: Phokion Kolaitis is a Distinguished Professor at the University of California Santa Cruz and a Principal Research Staff Member at the IBM Almaden Research Center. His research interests include principles of database systems, logic in computer science, and computational complexity.

Kolaitis is a Fellow of the American Association for the Advancement of Science (AAAS), a Fellow of the Association for Computing Machinery, a Foreign Member of the Finnish Academy of Science and Letters, a Foreign Member of Academia Europaea, and the recipient of a 1993 Guggenheim Fellowship. He is also the recipient of two IBM Research Division Outstanding Innovation Awards, an IBM Research Division Outstanding Technical Achievement Award, a co-winner of both the 2008 and the 2014 ACM PODS Alberto O. Mendelzon Test-of-Time Award, and a co-winner of the 2013 International Conference on Database Theory Test-of-Time Award.