Towards scalable data integration under constraints

In this paper we consider the problem of answering queries using views, with or without ontological constraints, which is important for data integration, query optimization, and data warehouses. Our context is data integration, so we search for maximally-contained rewritings. We have produced a very scalable and efficient solution for its simplest form, conjunctive queries and views, and we are working towards the full relational case. When considering constraints, the problem is usually divided in two phases: (1) query expansion, which rewrites queries w.r.t. the intentional knowledge and (2) expanded query reformulation using the views. Relevant algorithms have given little attention to the second phase and have studied a limited form of view definition languages overall (namely, only GAV). By looking at the problem from a graph perspective we are able to gain a better insight and develop designs which compactly represent common patterns in the source descriptions, and (optionally...

• Type: Journal
• Year: 2012
• Where: EDBT
• Authors: George Konstantinidis, José Luis Ambite
• Keywords: Art Algorithms, Database, EDBT 2012, Query Reformulation, Relevant Algorithms