Representing and Querying Incomplete Information: a Data Interoperability Perspective

This thesis is intended to be a succinct and rather informal presentation of some of my most recent work, which has been done in collaboration with several other people. In particular this thesis concentrates on our contributions to the study of incomplete information in the context of data interoperability. In this scenario data is heterogenous and decentralized, needs to be integrated from several sources and exchanged between different applications. Incompleteness, i.e. the presence of “missing” or “unknown” portions of data, is naturally generated in data exchange and integration, due to data heterogeneity. The management of incomplete information poses new challenges in this context. The focus of our study is the development of models of incomplete information suitable to data interoperability tasks, and the study of techniques for efficiently querying several forms of incompleteness. The work presented in Chapter 4 is ongoing in the context of Nadime Francis’s PhD, whom I am co-supervising together with Luc Segoufin.