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Book ChapterDOI

Query answering under non-guarded rules in datalog+/-

TLDR
The complexity of query answering under Datalog+/- class of decidable languages is investigated, and in addition the novel class of sticky-join sets of TGDs is presented, which generalizes both sticky sets ofTGDs and so-called linear TGDs, an extension of inclusion dependencies.
Abstract
In ontology-based data access, an extensional database is enhanced by an ontology that generates new intensional knowledge which has to be considered when answering queries. In this setting, tractable data complexity (i.e., complexity w.r.t. the data only) of query answering is crucial, given the need to deal with large data sets. A well-known class of tractable ontology languages is the DL-lite family; however, in DL-lite it is impossible to express simple and useful integrity constraints that involve joins. To overcome this limitation, the Datalog+/- class of decidable languages uses tuple-generating dependencies (TGDs) as rules, thus allowing for conjunctions of atoms in the rule bodies, with suitable limitations to ensure decidability. In particular, sticky sets of TGDs allow for joins and variable repetition in rule bodies under certain conditions. In this paper we extend the notion of stickiness by introducing weaklysticky sets of TGDs, which also generalize the well-known weakly-acyclic sets of TGDs. We investigate the complexity of query answering under such language, and in addition we provide novel complexity results on weakly-acyclic sets of TGDs. Moreover, we present the novel class of sticky-join sets of TGDs, which generalizes both sticky sets of TGDs and so-called linear TGDs, an extension of inclusion dependencies.

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Citations
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Proceedings ArticleDOI

A general datalog-based framework for tractable query answering over ontologies

TL;DR: It is shown in particular that Datalog+/- generalizes the DL-Lite family of tractable description logics, which are the most common tractable ontology languages in the context of the Semantic Web and databases.
Journal ArticleDOI

A general Datalog-based framework for tractable query answering over ontologies

TL;DR: It is shown how stratified negation can be added to Datalog^+/- while keeping ontology querying tractable, and paves the way for applying results from databases to the context of the Semantic Web.
Journal ArticleDOI

Towards more expressive ontology languages: The query answering problem

TL;DR: This paper studies novel relevant classes of ontological theories for which query answering is both decidable and of tractable data complexity, that is, the complexity with respect to the size of the data only, and obtains highly expressive and effective ontology languages that unify and generalize both classical database constraints and important features of the most widespread tractable description logics.
Proceedings ArticleDOI

Ontological queries: Rewriting and optimization

TL;DR: A new rewriting algorithm for rather general types of ontological constraints (description logics) and an effective new method that works for Linear Datalog±, a description logic that encompasses well-known description logics of the DL-Lite family are proposed.
Journal ArticleDOI

Advanced processing for ontological queries

TL;DR: A more expressive formalism that takes joins into account, while still enjoying the same low query-answering complexity is introduced, and a highly expressive and effective ontological modeling language that unifies and generalizes both classical database constraints and important features of the most widespread tractable description logics is obtained.
References
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Book

Foundations of databases

TL;DR: This book discusses Languages, Computability, and Complexity, and the Relational Model, which aims to clarify the role of Semantic Data Models in the development of Query Language Design.
Journal ArticleDOI

Tractable Reasoning and Efficient Query Answering in Description Logics: The DL-Lite Family

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.
Journal ArticleDOI

Data exchange: semantics and query answering

TL;DR: This paper gives an algebraic specification that selects, among all solutions to the data exchange problem, a special class of solutions that is called universal and shows that a universal solution has no more and no less data than required for data exchange and that it represents the entire space of possible solutions.
Book ChapterDOI

Linking data to ontologies

TL;DR: This paper presents a new ontology language, based on Description Logics, that is particularly suited to reason with large amounts of instances and a novel mapping language that is able to deal with the so-called impedance mismatch problem.
Journal ArticleDOI

Complexity and expressive power of logic programming

TL;DR: This article surveys various complexity and expressiveness results on different forms of logic programming, in particular, propositional logic programming and datalog, but it also mentions general logic programming with function symbols.
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