The DL-Lite Family and Relations

By Alessandro Artale, Diego Calvanese, Roman Kontchakov, Michael Zakharyaschev. Journal of Artificial Intelligence Research, 2009

613 citations recorded by the source corpus.

The recently introduced series of description logics under the common moniker 'DL-Lite' has attracted attention of the description logic and semantic web communities due to the low computational complexity of inference, on the one hand, and the ability to represent conceptual modeling formalisms, on the other. The main aim of this article is to carry out a thorough and systematic investigation of inference in extensions of the original DL-Lite logics along five axes: by (i) adding the Boolean connectives and (ii) number restrictions to concept constructs, (iii) allowing role hierarchies, (iv) allowing role disjointness, symmetry, asymmetry, reflexivity, irreflexivity and transitivity constraints, and (v) adopting or dropping the unique name assumption. We analyze the combined complexity of satisfiability for the resulting logics, as well as the data complexity of instance checking and answering positive existential queries. Our approach is based on embedding DL-Lite logics in suitable fragments of the one-variable first-order logic, which provides useful insights into their properties and, in particular, computational behavior.

Subfields: Artificial Intelligence, Computer Networks and Communications

View Paper: https://www.semanticscholar.org/paper/6156a7dea6f46cc12b9430808914dd169e262d1a

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Citations in the corpus

Description Logic Knowledge and Action Bases (2014, methodology): “i ] ∧ q = is a consequence of the construction by Artale et al. (2009), which shows that query entailment in the presence of equalities can be reduced to query evaluation by saturating equalities w.r.t. transitivity, reﬂexivity, symmetry, and functionality.”
Ontology-Based Data Access: A Survey (2018, methodology): “It is based on the DL-Lite family [ Calvanese et al. , 2007; Artale et al. , 2009 ] , a suite of DLs closely related to conceptual modelling formalisms for DB design and software engineering.”
Knowledge Graphs (2020, neutral): “The OWL 2 QL profile [362] is a subset of OWL designed specifically for query rewriting of this form [21].”
Taming the Infinite Chase: Query Answering under Expressive Relational Constraints (2008, methodology): “plexity. 10 Applications In this section we discuss applications of our results on weakly guarded sets of TGDs to Description Logic languages and object-oriented logic languages. 10.1 DL-Lite DL-Lite [27, 5] is a prominent family of ontology languages that has tractable query answering. Interestingl”
Knowledge-based Systems (2009, neutral): “We use data from a PVE conducted in 2020 to gauge the opinion of the residents of a municipality in the Netherlands over energy policies [41].”
A general datalog-based framework for tractable query answering over ontologies (2009, background): “, the DLLite family [34, 89] (which has recently been further extended in [8, 9]).”
Ontop: Answering SPARQL queries over relational databases (2016, methodology): “OWL 2 QL is based on the DL-Lite family of lightweight description logics [11,3], which guarantees that queries over the ontology can be rewritten into equivalent queries over the data alone.”