1,146 research outputs found
Inconsistency-tolerant Query Answering in Ontology-based Data Access
Ontology-based data access (OBDA) is receiving great attention as a new paradigm for managing information systems through semantic technologies. According to this paradigm, a Description Logic ontology provides an abstract and formal representation of the domain of interest to the information system, and is used as a sophisticated schema for accessing the data and formulating queries over them. In this paper, we address the problem of dealing with inconsistencies in OBDA. Our general goal is both to study DL semantical frameworks that are inconsistency-tolerant, and to devise techniques for answering unions of conjunctive queries under such inconsistency-tolerant semantics. Our work is inspired by the approaches to consistent query answering in databases, which are based on the idea of living with inconsistencies in the database, but trying to obtain only consistent information during query answering, by relying on the notion of database repair. We first adapt the notion of database repair to our context, and show that, according to such a notion, inconsistency-tolerant query answering is intractable, even for very simple DLs. Therefore, we propose a different repair-based semantics, with the goal of reaching a good compromise between the expressive power of the semantics and the computational complexity of inconsistency-tolerant query answering. Indeed, we show that query answering under the new semantics is first-order rewritable in OBDA, even if the ontology is expressed in one of the most expressive members of the DL-Lite family
Managing data through the lens of an ontology
Ontology-based data management aims at managing data through the lens of an ontology, that is, a conceptual representation of the domain of interest in the underlying information system. This new paradigm provides several interesting features, many of which have already been proved effective in managing complex information systems. This article introduces the notion of ontology-based data management, illustrating the main ideas underlying the paradigm, and pointing out the importance of knowledge representation and automated reasoning for addressing the technical challenges it introduces
A General Modifier-based Framework for Inconsistency-Tolerant Query Answering
We propose a general framework for inconsistency-tolerant query answering
within existential rule setting. This framework unifies the main semantics
proposed by the state of art and introduces new ones based on cardinality and
majority principles. It relies on two key notions: modifiers and inference
strategies. An inconsistency-tolerant semantics is seen as a composite modifier
plus an inference strategy. We compare the obtained semantics from a
productivity point of view
Datalog± Ontology Consolidation
Knowledge bases in the form of ontologies are receiving increasing attention as they allow to clearly represent both the available knowledge, which includes the knowledge in itself and the constraints imposed to it by the domain or the users. In particular, Datalog ± ontologies are attractive because of their property of decidability and the possibility of dealing with the massive amounts of data in real world environments; however, as it is the case with many other ontological languages, their application in collaborative environments often lead to inconsistency related issues. In this paper we introduce the notion of incoherence regarding Datalog± ontologies, in terms of satisfiability of sets of constraints, and show how under specific conditions incoherence leads to inconsistent Datalog ± ontologies. The main contribution of this work is a novel approach to restore both consistency and coherence in Datalog± ontologies. The proposed approach is based on kernel contraction and restoration is performed by the application of incision functions that select formulas to delete. Nevertheless, instead of working over minimal incoherent/inconsistent sets encountered in the ontologies, our operators produce incisions over non-minimal structures called clusters. We present a construction for consolidation operators, along with the properties expected to be satisfied by them. Finally, we establish the relation between the construction and the properties by means of a representation theorem. Although this proposal is presented for Datalog± ontologies consolidation, these operators can be applied to other types of ontological languages, such as Description Logics, making them apt to be used in collaborative environments like the Semantic Web.Fil: Deagustini, Cristhian Ariel David. Consejo Nacional de Investigaciones CientÃficas y Técnicas. Centro CientÃfico Tecnológico Conicet - BahÃa Blanca. Instituto de Ciencias e IngenierÃa de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e IngenierÃa de la Computación. Instituto de Ciencias e IngenierÃa de la Computación; ArgentinaFil: Martinez, Maria Vanina. Consejo Nacional de Investigaciones CientÃficas y Técnicas. Centro CientÃfico Tecnológico Conicet - BahÃa Blanca. Instituto de Ciencias e IngenierÃa de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e IngenierÃa de la Computación. Instituto de Ciencias e IngenierÃa de la Computación; ArgentinaFil: Falappa, Marcelo Alejandro. Consejo Nacional de Investigaciones CientÃficas y Técnicas. Centro CientÃfico Tecnológico Conicet - BahÃa Blanca. Instituto de Ciencias e IngenierÃa de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e IngenierÃa de la Computación. Instituto de Ciencias e IngenierÃa de la Computación; ArgentinaFil: Simari, Guillermo Ricardo. Consejo Nacional de Investigaciones CientÃficas y Técnicas. Centro CientÃfico Tecnológico Conicet - BahÃa Blanca. Instituto de Ciencias e IngenierÃa de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e IngenierÃa de la Computación. Instituto de Ciencias e IngenierÃa de la Computación; Argentin
Inconsistency Handling in Ontology-Mediated Query Answering: A Progress Report
International audienceThis paper accompanies an invited talk on inconsistency handling in OMQA and presents a concise summary of the research that has been conducted in the area
Exchange-Repairs: Managing Inconsistency in Data Exchange
In a data exchange setting with target constraints, it is often the case that
a given source instance has no solutions. In such cases, the semantics of
target queries trivialize. The aim of this paper is to introduce and explore a
new framework that gives meaningful semantics in such cases by using the notion
of exchange-repairs. Informally, an exchange-repair of a source instance is
another source instance that differs minimally from the first, but has a
solution. Exchange-repairs give rise to a natural notion of exchange-repair
certain answers (XR-certain answers) for target queries. We show that for
schema mappings specified by source-to-target GAV dependencies and target
equality-generating dependencies (egds), the XR-certain answers of a target
conjunctive query can be rewritten as the consistent answers (in the sense of
standard database repairs) of a union of conjunctive queries over the source
schema with respect to a set of egds over the source schema, making it possible
to use a consistent query-answering system to compute XR-certain answers in
data exchange. We then examine the general case of schema mappings specified by
source-to-target GLAV constraints, a weakly acyclic set of target tgds and a
set of target egds. The main result asserts that, for such settings, the
XR-certain answers of conjunctive queries can be rewritten as the certain
answers of a union of conjunctive queries with respect to the stable models of
a disjunctive logic program over a suitable expansion of the source schema.Comment: 29 pages, 13 figures, submitted to the Journal on Data Semantic
Complexity of Inconsistency-Tolerant Query Answering in Datalog+/- under Cardinality-Based Repairs
This is the author accepted manuscript. The final version is available from Association for the Advancement of Artificial Intelligence (AAAI) via the link in this recordQuerying inconsistent ontological knowledge bases is an important
problem in practice, for which several inconsistencytolerant
query answering semantics have been proposed, including
query answering relative to all repairs, relative to
the intersection of repairs, and relative to the intersection of
closed repairs. In these semantics, one assumes that the input
database is erroneous, and the notion of repair describes a
maximally consistent subset of the input database, where different
notions of maximality (such as subset and cardinality
maximality) are considered. In this paper, we give a precise
picture of the computational complexity of inconsistencytolerant
(Boolean conjunctive) query answering in a wide
range of Datalog± languages under the cardinality-based versions
of the above three repair semantics.This work was supported by the Alan
Turing Institute under the UK EPSRC grant EP/N510129/1,
and by the EPSRC grants EP/R013667/1, EP/L012138/1,
and EP/M025268/1
Complexity of Approximate Query Answering under Inconsistency in Datalog+/-
This is the author accepted manuscript. The final version is freely available from IJCAI via the link in this recordSeveral semantics have been proposed to query inconsistent
ontological knowledge bases, including
the intersection of repairs and the intersection of
closed repairs as two approximate inconsistencytolerant
semantics. In this paper, we analyze the
complexity of conjunctive query answering under
these two semantics for a wide range of Datalog±
languages. We consider both the standard setting,
where errors may only be in the database, and the
generalized setting, where also the rules of a Datalog±
knowledge base may be erroneous.This work was supported by The Alan Turing Institute under
the UK EPSRC grant EP/N510129/1, and by the EPSRC
grants EP/R013667/1, EP/L012138/1, and EP/M025268/1
Complexity of Inconsistency-Tolerant Query Answering in Datalog+/- under Cardinality-Based Repairs
Querying inconsistent ontological knowledge bases is an important problem in practice, for which
several inconsistency-tolerant semantics have been proposed. In these semantics, the input database is
erroneous, and a repair is a maximally consistent database subset. Different notions of maximality (such
as subset and cardinality maximality) have been considered. In this paper, we give a precise picture of
the computational complexity of inconsistency-tolerant query answering in a wide range of Datalog+/–
languages under the cardinality-based versions of three prominent repair semantic
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