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Ontology-based data integration

About: Ontology-based data integration is a research topic. Over the lifetime, 11065 publications have been published within this topic receiving 216888 citations.


Papers
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Proceedings ArticleDOI
23 Aug 2004
TL;DR: The proposed evaluation strategy is to provide a detailed quantitative analysis of the ontology learning algorithms, in order to compute the accuracy of OntoLearn under different learning circumstances.
Abstract: Ontology evaluation is a critical task, even more so when the ontology is the output of an automatic system, rather than the result of a conceptualisation effort produced by a team of domain specialists and knowledge engineers. This paper provides an evaluation of the OntoLearn ontology learning system. The proposed evaluation strategy is twofold: first, we provide a detailed quantitative analysis of the ontology learning algorithms, in order to compute the accuracy of OntoLearn under different learning circumstances. Second, we automatically generate natural language descriptions of formal concept specifications, in order to facilitate per-concept qualitative analysis by domain specialists.

50 citations

Journal ArticleDOI
TL;DR: This study aims to review ontology research to explore its trends, gaps, and opportunities in the construction industry and to reduce arbitrariness and subjectivity involved in research topic analysis.
Abstract: Being information-intensive, the construction industry has the feature of multiagents, including multiparticipants from different disciplines, multiprocesses with a long-span timeline, and multidocuments generated by various systems. The multistakeholder context of the construction industry creates problems such as poor information interoperability and low productivity arising from difficulties in information reuse. Many researchers have explored the use of ontology to address these issues. This study aims to review ontology research to explore its trends, gaps, and opportunities in the construction industry. A systematic process employing three-phase search method, objective analysis and subjective analysis, helps to provide enough potential articles related to construction ontology research, and to reduce arbitrariness and subjectivity involved in research topic analysis. As a result, three main research topics aligned with the ontology development lifecycle were derived as follows: information ...

50 citations

Journal ArticleDOI
TL;DR: An ontology-based framework for IDA that has a modular design that facilitates the integration, exchange and reuse of its constitutive parts is presented and it is shown how complex temporal patterns that combine several variables and representation schemes can be used to infer process states and/or conditions.
Abstract: In the past years, the large availability of sensed data highlighted the need of computer-aided systems that perform intelligent data analysis (IDA) over the obtained data streams. Temporal abstractions (TAs) are key to interpret the principle encoded within the data, but their usefulness depends on an efficient management of domain knowledge. In this article, an ontology-based framework for IDA is presented. It is based on a knowledge model composed by two existing ontologies (Semantic Sensor Network ontology (SSN), SWRL Temporal Ontology (SWRLTO)) and a new developed one: the Temporal Abstractions Ontology (TAO). SSN conceptualizes sensor measurements, thus enabling a full integration with semantic sensor web (SSW) technologies. SWRLTO provides temporal modeling and reasoning. TAO has been designed to capture the semantic of TAs. These ontologies have been aligned through DOLCE Ultra-Lite (DUL) upper ontology, boosting the integration with other domains. The resulting knowledge model has a modular design that facilitates the integration, exchange and reuse of its constitutive parts. The framework is sketched in a chemical plant case study. It is shown how complex temporal patterns that combine several variables and representation schemes can be used to infer process states and/or conditions.

50 citations

Journal ArticleDOI
TL;DR: This study shows that it is possible to represent operational definitions of diseases with OWL and successfully classify real patient cases and Representing diagnostic criteria as descriptive knowledge allows us to take advantage of tools already available for OWL.
Abstract: Ontology and associated generic tools are appropriate for knowledge modeling and reasoning, but most of the time, disease definitions in existing description logic (DL) ontology are not sufficient to classify patient's characteristics under a particular disease because they do not formalize operational definitions of diseases (association of signs and symptoms=diagnostic criteria). The main objective of this study is to propose an ontological representation which takes into account the diagnostic criteria on which specific patient conditions may be classified under a specific disease. This method needs as a prerequisite a clear list of necessary and sufficient diagnostic criteria as defined for lots of diseases by learned societies. It does not include probability/uncertainty which Web Ontology Language (OWL 2.0) cannot handle. We illustrate it with spondyloarthritis (SpA). Ontology has been designed in Protege 4.1 OWL-DL2.0. Several kinds of criteria were formalized: (1) mandatory criteria, (2) picking two criteria among several diagnostic criteria, (3) numeric criteria. Thirty real patient cases were successfully classified with the reasoner. This study shows that it is possible to represent operational definitions of diseases with OWL and successfully classify real patient cases. Representing diagnostic criteria as descriptive knowledge (instead of rules in Semantic Web Rule Language or Prolog) allows us to take advantage of tools already available for OWL. While we focused on Assessment of SpondyloArthritis international Society SpA criteria, we believe that many of the representation issues addressed here are relevant to using OWL-DL for operational definition of other diseases in ontology.

50 citations

Patent
19 Sep 2011
TL;DR: In this paper, a system gathers information on important and influential people and uses an ontology to build a social graph, which is organized based on this social graph and provided to users as a service.
Abstract: A system gathers information on important and influential people and uses an ontology to build a social graph. The information is organized based on this social graph and provided to users as a service. The system uses ontology models to identify connectivity between entities (e.g., people, organizations, events, and things) in the social graph. Through its ontology, the system can determine, interpret, and represent the relationships of people that occur in the real world.

50 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202337
2022149
202111
202011
201919
201843