1,721,012 research outputs found
Data Quality in Ontology-based Data Access: The Case of Consistency
Full text linkOntology-based data access (OBDA) is a new paradigm aiming at accessing and managing data by means of an ontology, i.e., a conceptual representation of the domain of interest in the underlying information system. In the last years, this new paradigm has been used for providing users with abstract (independent from technological and system-oriented aspects), effective, and reasoning-intensive mechanisms for querying the data residing at the information system sources. In this paper we argue that OBDA, besides querying data, provides the right principles for devising a formal approach to data quality. In particular, we concentrate on one of the most important dimensions considered both in the literature and in the practice of data quality, namely consistency. We define a general framework for data consistency in OBDA, and present algorithms and complexity analysis for several relevant tasks related to the problem of checking data quality under this dimension, both at the extensional level (content of the data sources), and at the intensional level (schema of the data sources)
Epistemic Integrity Constraints for Ontology-Based Data Management
Full text linkOntology-based data management (OBDM) is a powerful knowledge-oriented paradigm for managing data spread over multiple heterogeneous sources. In OBDM, the data sources of an information system are handled through the reconciled view provided by an ontology, i.e., the conceptualization of the underlying domain of interest expressed in some formal language. In any information systems where the basic knowledge resides in data sources, it is of paramount importance to specify the acceptable states of such information. Usually, this is done via integrity constraints, i.e., requirements that the data must satisfy formally expressed in some specific language. However, while the semantics of integrity constraints are clear in the context of databases, the presence of inferred information, typical of OBDM systems, considerably complicates the matter. In this paper, we establish a novel framework for integrity constraints in the OBDM scenarios, based on the notion of knowledge state of the information system. For integrity constraints in this framework, we define a language based on epistemic logic, and study decidability and complexity of both checking satisfaction and performing different forms of static analysis on them
Maria ELEFANTE (a cura di), Velleio Patercolo. I due libri al console Marco Vinicio.
No full textDesy Philippe. Maria ELEFANTE (a cura di), Velleio Patercolo. I due libri al console Marco Vinicio. . In: L'antiquité classique, Tome 72, 2003. p. 401
Monotone Abstractions in Ontology-Based Data Management
Full text linkIn Ontology-Based Data Management (OBDM), an abstraction of a source query q is a query over the ontology capturing the semantics of q in terms of the concepts and the relations available in the ontology. Since a perfect characterization of a source query may not exist, the notions of best sound and complete approximations of an abstraction have been introduced and studied in the typical OBDM context, i.e., in the case where the ontology is expressed in DL-Lite, and source queries are expressed as unions of conjunctive queries (UCQs). Interestingly, if we restrict our attention to abstractions expressed as UCQs, even best approximations of abstractions are not guaranteed to exist. Thus, a natural question to ask is whether such limitations affect even larger classes of queries. In this paper, we answer this fundamental question for an essential class of queries, namely the class of monotone queries. We define a monotone query language based on disjunctive Datalog enriched with an epistemic operator, and show that its expressive power suffices for expressing the best approximations of monotone abstractions of UCQs
Synthesizing extensional constraints in Ontology-based Data Access
No full textSeveral recent techniques and tools for Ontology-based Data Access (OBDA) make use of the so-called extensional constraints (a.k.a. ABox dependencies). So far, extensional constraints have been mainly considered in a setting where data are represented in an ABox, instead of external data sources connected to the ontology through declarative mappings. Moreover, the issue of how to generate extensional constraints in practice has not been addressed yet. In this paper we first provide a formal account of the notion of extensional constraints in a full-fledged OBDA setting, where an ontology is connected to the data sources of the information system by means of mappings, and then present an approach to the automatic generation of extensional constraints in such a setting. The technique we propose is based on the use of a first-order theorem prover that checks validity of relevant formulas built over the mapping views. The experiments we have carried out in real-world OBDA projects show the effectiveness of our approach in discovering large collections of extensional constraints entailed by the OBDA specification
Reducing global consistency to local consistency in Ontology-based Data Access
No full textOntology-based data access (OBDA) is a paradigm aiming at accessing and managing the data of an information system by means of an ontology [6]. An OBDA system is constituted by an OBDA specification, representing its intensional level, and one or more data sources, representing the extensional one. Depending on the relation th
Velleio Patercolo, I due libri al console Marco Vinicio. Introd., testo e trad, a cura di M. Elefante, 1999
No full textDeschamps Lucienne. Velleio Patercolo, I due libri al console Marco Vinicio. Introd., testo e trad, a cura di M. Elefante, 1999. In: Revue des Études Anciennes. Tome 103, 2001, n°3-4. p. 564
Efficient approximation in DL-Lite of OWL 2 ontologies
No full textOntologies, as a conceptualization of a domain of interest, can be used for different objectives, such as for providing a formal description of the domain of interest for documentation purposes, or for providing a mechanism for reasoning upon the domain. For instance, they are the core element of the Ontology-Based Data Access paradigm, in which the ontology is utilized as a conceptual view, allowing user access to the underlying data sources. With the aim to use an ontology as a formal description of the domain of interest, the use of expressive languages proves to be useful. If instead the goal is to use the ontology for reasoning tasks which require low computational complexity, the high expressivity of the language used to model the ontology may be of hindrance. In this scenario, the approximation of ontologies expressed in very expressive languages through ontologies expressed in languages which keep the computational complexity of the reasoning tasks low is pivotal. In this work we present our notion of ontology approximation and present an algorithm for computing the approximation of OWL 2 ontologies by means of DL-Lite TBoxes. Moreover, we provide optimization techniques for this computation, and discuss the results of the implementation of these techniques
What Does a Query Answer Tell You? Informativeness of Query Answers for Knowledge Bases
Full text linkQuery answering for Knowledge Bases (KBs) amounts to extracting information from the various models of a KB, and presenting the user with an object that represents such information. In the vast majority of cases, this object consists of those tuples of constants that satisfy the query expression either in every model (certain answers) or in some model (possible answers). However, similarly to the case of incomplete databases, both these forms of answers are a lossy representation of all the knowledge inferable from the query and the queried KB. In this paper, we illustrate a formal framework to characterize the information that query answers for KBs are able to represent. As a frst application of the framework, we study the informativeness of current query answering approaches, including the recently introduced partial answers. We then defne a novel notion of answers, allowing repetition of variables across answer tuples. We show that these answers are capable of representing a meaningful form of information, and we also study their data complexity properties
My (Fair) Big Data
No full textPolicy making has the strict requirement to rely on quantitative and high quality information. This paper will address the data quality issue for policy making by showing how to deal with Big Data quality in the different steps of a processing pipeline, with a focus on the integration of Big Data sources with traditional sources. In this respect, a relevant role is played by metadata and in particular by ontologies. Integration systems relying on ontologies enable indeed a formal quality evaluation of inaccuracy, inconsistency and incompleteness of integrated data. The paper will finally describe data confidentiality as a Big Data quality dimension, showing the main issues to be faced for its assurance
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