PAGOdA: Pay-As-You-Go Ontology Query Answering Using a Datalog Reasoner

Zhou, Yonghui; Grau, Bernardo Cuenca; Nenov, Yavor; Kaminski, Mark; Horrocks, Ian

doi:10.1613/jair.4757

Cited by 44 publications

(52 citation statements)

References 68 publications

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“…Both aw 0 · · · w n −1 and σv 1 · · · v m are instances of B n−1 . By (10) and (16) (6), right(Q) = left(S ). Consider the atom B n−2 (x n−2 ) from q r n .…”

Section: Discussionmentioning

confidence: 99%

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Query inseparability for ALC ontologies

Botoeva

Lutz

Ryzhikov

et al. 2019

Artificial Intelligence

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We investigate the problem whether two ALC ontologies are indistinguishable (or inseparable) by means of queries in a given signature, which is fundamental for ontology engineering tasks such as ontology versioning, modularisation, update, and forgetting. We consider both knowledge base (KB) and TBox inseparability. For KBs, we give modeltheoretic criteria in terms of (finite partial) homomorphisms and products and prove that this problem is undecidable for conjunctive queries (CQs), but 2ExpTime-complete for unions of CQs (UCQs). The same results hold if (U)CQs are replaced by rooted (U)CQs, where every variable is connected to an answer variable. We also show that inseparability by CQs is still undecidable if one KB is given in the lightweight DL EL and if no restrictions are imposed on the signature of the CQs. We also consider the problem whether two ALC TBoxes give the same answers to any query over any ABox in a given signature and show that, for CQs, this problem is undecidable, too. We then develop model-theoretic criteria for HornALC TBoxes and show using tree automata that, in contrast, inseparability becomes decidable and 2ExpTime-complete, even ExpTime-complete when restricted to (unions of) rooted CQs. module is extracted from an ontology. In ontology update or revision, the difference between the answers to queries over the updated or revised ontology and the original one should be minimised when constructing update or revision operators. Similarly, in forgetting, it is the answers to queries which should be preserved under appropriate forgetting operators. Thus, in the context of query answering, the fundamental relationship between ontologies is not whether they are logically equivalent (have the same models), but whether they give the same answers to any relevant query. To illustrate, consider the following simple TBox T = {Book ∃author.¬Book} saying that every book has an author who is not a book. Clearly, T is not logically equivalent to the TBoxwhich only states that every book has an author. However, if one takes as the query language the popular classes of conjunctive queries (CQs) or unions of CQs (UCQs), then no matter what the data is, every query will have the same answers independently of whether one uses T or T . Intuitively, the reason is that the 'positive' information given by T coincides with the 'positive' information given by T . If the main purpose of the ontology is answering UCQs, it is thus more important to know that T can be safely replaced by T without affecting the answers to UCQs than to establish that T and T are not logically equivalent.In most ontology engineering applications for ontology-based data access, the relevant class Q of queries can be further restricted to those given in a finite signature of relevant concept and role names. For example, to establish that a subset M of an ontology O is a module of O, one should not require that M and O give the same answers to all queries in Q, but only to those that are in the signature of M. Similarly, in the versioning ...

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“…Both aw 0 · · · w n −1 and σv 1 · · · v m are instances of B n−1 . By (10) and (16) (6), right(Q) = left(S ). Consider the atom B n−2 (x n−2 ) from q r n .…”

Section: Discussionmentioning

confidence: 99%

“…By considering B n−2 (x n−2 ) in q n , we obtain that both aw 0 · · · w n−2 and σv 1 · · · v m−1 are instances of B n−2 . By (10) and (16), B n−2 = Q 1 and down(U) = up(Q).…”

Section: Undecidability Of (R)cq-entailment and Inseparability For Almentioning

confidence: 94%

Query inseparability for ALC ontologies

Botoeva

Lutz

Ryzhikov

et al. 2019

Artificial Intelligence

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“…Ideally, one would show that the simpler ontology is equivalent to the original with regards to query answering [17], and thus provides the exact set of answers. Alternatively, one can use a simpler ontology to approximate the answers for the full one [17,28] (possibly employing a more costly complete algorithm to decide the status of the remaining candidate answers [89]). Theorem 3.9.…”

Section: Conclusion and Open Problemsmentioning

confidence: 99%

Ontology-Mediated Queries

Bienvenu

Kikot

Kontchakov

et al. 2018

J. ACM

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We give solutions to two fundamental computational problems in ontology-based data access with the W3C standard ontology language OWL 2 QL: the succinctness problem for first-order rewritings of ontology-mediated queries (OMQs), and the complexity problem for OMQ answering. We classify OMQs according to the shape of their conjunctive queries (treewidth, the number of leaves) and the existential depth of their ontologies. For each of these classes, we determine the combined complexity of OMQ answering, and whether all OMQs in the class have polynomial-size first-order, positive existential and nonrecursive datalog rewritings. We obtain the succinctness results using hypergraph programs, a new computational model for Boolean functions, which makes it possible to connect the size of OMQ rewritings and circuit complexity.

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“…For example, the authors of [212] first use a Datalog reasoner to approximate the answers both from below and from above. For example, the authors of [212] first use a Datalog reasoner to approximate the answers both from below and from above.…”

Section: Extending the Applicability Of Horn DL Techniquesmentioning

confidence: 99%