Topic
Abox
About: Abox is a research topic. Over the lifetime, 400 publications have been published within this topic receiving 10607 citations. The topic is also known as: Abox.
Papers published on a yearly basis
Papers
TL;DR: It is shown that, for the DLs of the DL-Lite family, the usual DL reasoning tasks are polynomial in the size of the TBox, and query answering is LogSpace in thesize of the ABox, which is the first result ofPolynomial-time data complexity for query answering over DL knowledge bases.
Abstract: We propose a new family of description logics (DLs), called DL-Lite, specifically tailored to capture basic ontology languages, while keeping low complexity of reasoning. Reasoning here means not only computing subsumption between concepts and checking satisfiability of the whole knowledge base, but also answering complex queries (in particular, unions of conjunctive queries) over the instance level (ABox) of the DL knowledge base. We show that, for the DLs of the DL-Lite family, the usual DL reasoning tasks are polynomial in the size of the TBox, and query answering is LogSpace in the size of the ABox (i.e., in data complexity). To the best of our knowledge, this is the first result of polynomial-time data complexity for query answering over DL knowledge bases. Notably our logics allow for a separation between TBox and ABox reasoning during query evaluation: the part of the process requiring TBox reasoning is independent of the ABox, and the part of the process requiring access to the ABox can be carried out by an SQL engine, thus taking advantage of the query optimization strategies provided by current database management systems. Since even slight extensions to the logics of the DL-Lite family make query answering at least NLogSpace in data complexity, thus ruling out the possibility of using on-the-shelf relational technology for query processing, we can conclude that the logics of the DL-Lite family are the maximal DLs supporting efficient query answering over large amounts of instances.
1,691 citations
Proceedings Article•
2 Jun 2006TL;DR: In this article, the authors study the data complexity of answering conjunctive queries over Description Logic knowledge bases and show that the Description Logics of the DL-Lite family are the maximal logics that allow query answering over very large ABoxes.
Abstract: In this paper we study data complexity of answering conjunctive queries over Description Logic knowledge bases constituted by an ABox and a TBox. In particular, we are interested in characterizing the FOL-reducibility and the polynomial tractability boundaries of conjunctive query answering, depending on the expressive power of the Description Logic used to specify the knowledge base. FOL-reducibility means that query answering can be reduced to evaluating queries over the database corresponding to the ABox. Since first-order queries can be expressed in SQL, the importance of FOL-reducibility is that, when query answering enjoys this property, we can take advantage of Data Base Management System (DBMS) techniques for both representing data, i.e., ABox assertions, and answering queries via reformulation into SQL. What emerges from our complexity analysis is that the Description Logics of the DL-Lite family are the maximal logics allowing conjunctive query answering through standard database technology. In this sense, they are the first Description Logics specifically tailored for effective query answering over very large ABoxes.
446 citations
Proceedings Article•
1 Jan 2007TL;DR: SPARQL-DL is a substantial subset of SPARQL for which it provides a clear OWL-DL based semantics and is significantly more expressive than existing DL QLs and can still be implemented without too much effort on top of existing OWl-DL reasoners.
Abstract: There are many query languages (QLs) that can be used to query RDF and OWL ontologies but neither type is satisfactory for querying OWL-DL ontologies. RDF-based QLs (RDQL, SeRQL, SPARQL) are harder to give a semantics w.r.t. OWL-DL and are more powerful than what OWL-DL reasoners can provide. DL-based QLs (DIG ask queries, nRQL) have clear semantics but are not powerful enough in the general case. In this paper we describe SPARQL-DL, a substantial subset of SPARQL for which we provide a clear OWL-DL based semantics. SPARQL-DL is significantly more expressive than existing DL QLs (by allowing mixed TBox/RBox/ABox queries) and can still be implemented without too much effort on top of existing OWL-DL reasoners. We discuss design decisions and practical issues that arise for defining SPARQL-DL and report about our preliminary prototype implemented on top of OWL-DL reasoner Pellet.
300 citations
17 Jun 2000
TL;DR: An algorithm for combined Tbox and Abox reasoning in the \(\mathcal{SHIQ}\) description logic is presented, of particular interest as it can be used to decide the problem of (database) conjunctive query containment w.r.t. a schema.
Abstract: While there has been a great deal of work on the development of reasoning algorithms for expressive description logics, in most cases only Tbox reasoning is considered. In this paper we present an algorithm for combined Tbox and Abox reasoning in the \(\mathcal{SHIQ}\) description logic. This algorithm is of particular interest as it can be used to decide the problem of (database) conjunctive query containment w.r.t. a schema. Moreover, the realisation of an efficient implementation should be relatively straightforward as it can be based on an existing highly optimised implementation of the Tbox algorithm in the FaCT system.
280 citations
Proceedings Article•
25 Jul 2015TL;DR: In this article, the authors study the data complexity of answering conjunctive queries over Description Logic knowledge bases, and show that the Description Logics of the DL-Lite family are essentially the maximal logics allowing for conjunective query answering through standard database technology.
Abstract: We study the data complexity of answering conjunctive queries over Description Logic knowledge bases constituted by a TBox and an ABox. In particular, we are interested in characterizing the FO-rewritability and the polynomial tractability boundaries of conjunctive query answering, depending on the expressive power of the DL used to express the knowledge base. What emerges from our complexity analysis is that the Description Logics of the DL-Lite family are essentially the maximal logics allowing for conjunctive query answering through standard database technology.
272 citations
Related Topics (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2021 | 13 |
| 2020 | 14 |
| 2019 | 12 |
| 2018 | 20 |
| 2017 | 20 |
| 2016 | 19 |