Conjunctive Query Answering for the Description Logic SHIQ

Glimm, Birte; Horrocks, Ian; Lutz, Carsten; Sattler, Ulrike

doi:10.1613/jair.2372

Cited by 153 publications

(182 citation statements)

References 31 publications

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“…In particular, the above theorem and the results on CQ/UCQ containment in DLs presented in [20,7,15,25] imply the following property: for all the DLs studied in this paper, NM-satisfiability (as well as FOL-satisfiability) of weakly DL-safe r-hybrid KBs is decidable.…”

Section: Results For Weakly Dl-safe Rulesmentioning

confidence: 60%

“…-the results for NR-Datalog programs follow from Theorem 1 and from the results in [6,13]; -the well-known translation of arbitrary first-order queries in NR-Datalog ¬ allows for reducing satisfiability of first-order sentences to satisfiability of r-hybrid KBs with NR-Datalog ¬ programs for any choice of the DL language, which immediately implies undecidability of reasoning in this class of r-hybrid KBs.…”

Section: Theorem 5 Let H = (K P) Be a R-hybrid Kb Such That P Is A mentioning

confidence: 89%

“…The only known studies related to this topic are the work on CARIN [20], which has shown decidability of nonrecursive positive Datalog with the DL ALCN R, and the studies on conjunctive query answering in DLs (see e.g. [7,24,25,14,15]), which are indirectly related to integrating Datalog and DLs (since conjunctive queries can be seen as nonrecursive Datalog programs consisting of a single rule).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

On Combining Description Logic Ontologies and Nonrecursive Datalog Rules

Rosati

2008

Web Reasoning and Rule Systems

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Abstract. Reasoning in systems integrating Description Logics (DL) ontologies and Datalog rules is a very hard task, and previous studies have shown undecidability of reasoning in systems integrating (even very simple) DL ontologies with recursive Datalog. However, the results obtained so far constitute a very partial picture of the computational properties of systems combining DL ontologies and Datalog rules. The aim of this paper is to contribute to complete this picture, extending the computational analysis of reasoning in systems integrating ontologies and Datalog rules. More precisely, we first provide a set of decidability and complexity results for reasoning in systems combining ontologies specified in DLs and rules specified in nonrecursive Datalog (and its extensions with inequality and negation): such results identify, from the viewpoint of the expressive abilities of the two formalisms, minimal combinations of Description Logics and Datalog in which reasoning is undecidable. Then, we present new results on the decidability and complexity of the so-called restricted (or safe) integration of DL ontologies and Datalog rules. Our results show that: (1) the unrestricted interaction between DLs and Datalog is computationally very hard even in the absence of recursion in rules; (2) surprisingly, the various "safeness" restrictions, which have been defined to regain decidability of reasoning in the interaction between DLs and recursive Datalog, appear as necessary restrictions even when rules are not recursive.

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Section: Results For Weakly Dl-safe Rulesmentioning

confidence: 60%

Section: Theorem 5 Let H = (K P) Be a R-hybrid Kb Such That P Is A mentioning

confidence: 89%

Section: Introductionmentioning

confidence: 99%

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On Combining Description Logic Ontologies and Nonrecursive Datalog Rules

Rosati

2008

Web Reasoning and Rule Systems

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“…We use the term query in the remainder for such BGPs. W.l.o.g., we assume that queries are connected [2]. Let q = {at 1 , .…”

Section: Preliminariesmentioning

confidence: 99%

Cost Based Query Ordering over OWL Ontologies

Kollia

Glimm

2012

The Semantic Web – ISWC 2012

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Abstract. The paper presents an approach for cost-based query planning for SPARQL queries issued over an OWL ontology using the OWL Direct Semantics entailment regime of SPARQL 1.1. The costs are based on information about the instances of classes and properties that are extracted from a model abstraction built by an OWL reasoner. A static and a dynamic algorithm are presented which use these costs to find optimal or near optimal execution orders for the atoms of a query. For the dynamic case, we improve the performance by exploiting an individual clustering approach that allows for computing the cost functions based on one individual sample from a cluster. Our experimental study shows that the static ordering usually outperforms the dynamic one when accurate statistics are available. This changes, however, when the statistics are less accurate, e.g., due to non-deterministic reasoning decisions.

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“…Unfortunately, query answering over OWL 2 DL ontologies is of very high computational complexity [3,4] and even after modern optimisations and intense implementation efforts [5] OWL 2 DL systems are still not able to cope with datasets containing billions of data.…”

Section: Introductionmentioning

confidence: 99%

Hydrowl: A Hybrid Query Answering System for OWL 2 DL Ontologies

Stoilos

2014

Web Reasoning and Rule Systems

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Abstract. This system description paper introduces the OWL 2 query answering system Hydrowl. Hydrowl is based on novel hybrid techniques which in order to compute the query answers combine at run-time a reasoner ans1 supporting a (tractable) fragment of OWL 2 (e.g., OWL 2 QL and OWL 2 RL) with a fully-fledged OWL 2 DL reasoner ans2. The motivation is that if most of the (query answering) work is delegated to the (usually) very scalable system ans1 while the interaction with ans2 is kept to a bare minimum, then we can possibly provide with scalable query answering even over expressive fragments of OWL 2 DL. We discuss the system's architecture and we present an overview of the techniques used. Finally, we present some first encouraging experimental results.

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Conjunctive Query Answering for the Description Logic SHIQ

Cited by 153 publications

References 31 publications

On Combining Description Logic Ontologies and Nonrecursive Datalog Rules

On Combining Description Logic Ontologies and Nonrecursive Datalog Rules

Cost Based Query Ordering over OWL Ontologies

Hydrowl: A Hybrid Query Answering System for OWL 2 DL Ontologies

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