Metamodeling and metaquerying are gaining momentum in the context of both conceptual modeling and semantic web. Indeed it has been largely recognized that metamodeling represents a very useful tool to formalize complex patterns involving elements of the domain of interest, that otherwise are forced to be excluded from the modeling process, and a number of languages equipped with a spectrum of metamodeling features have been studied. However, it has been recognized as well, that the benefit of using metamodeling is greatly limited if one cannot use metaquerying as tool for extracting knowledge deriving from such meta-level patterns. Unfortunately, at the moment, no system exists that correctly manages metamodeling and metaquerying. The goal of this work is precisely to fill this gap by introducing a system, called MQ-Mastro, that allows metaquerying over ontologies expressed in a language of the OWL 2 family equipped with a semantics appropriate for metamodeling.
2020, INFORMATION SYSTEMS, Pages 1-16 (volume: 88)
Metaquerying made practical for OWL 2 QL ontologies (01a Articolo in rivista)
Lenzerini Maurizio, Lepore Lorenzo, Poggi Antonella
Gruppo di ricerca: Artificial Intelligence and Knowledge Representation, Gruppo di ricerca: Data Management and Semantic Technologies