Data integration provides a unified and abstract view over a set of existing data sources. The typical architecture of a data integration system comprises the global schema, which is the structure for the unified view, the source schema, and the mapping, which is a formal account of how data at the sources relate to the global view. Most of the research work on data integration in the last decades deals with the problem of processing a query expressed on the global schema by computing a suitable query over the sources, and then evaluating the latter in order to derive the answers to the original query. Here, we address a novel issue in data integration: starting from a query expressed over the sources, the goal is to find an abstraction of such query, i.e., a query over the global schema that captures the original query, modulo the mapping. The goal of the paper is to provide an overview of the notion of abstraction in data integration, by presenting a formal framework, illustrating the results that have appeared in the recent literature, and discussing interesting directions for future research.
2021, 2021 36th Annual ACM/IEEE Symposium on Logic in Computer Science (LICS), Pages 1-11 (volume: 2021-)
Abstraction in Data Integration (04b Atto di convegno in volume)
Cima G., Console M., Lenzerini M., Poggi A.
Gruppo di ricerca: Artificial Intelligence and Knowledge Representation, Gruppo di ricerca: Data Management and Semantic Technologies