Search results for "OWL ontology"

showing 5 items of 5 documents

Probabilistic techniques for bridging the semantic gap in schema alignment

Connecting pieces of informations from heterogeneous sources sharing the same domain is an open challenge in Semantic Web, Big Data and business communities. The main problem in this research area is to bridge the expressiveness gap between relational databases and ontologies. In general, an ontology is more expressive and captures more semantic information behind data than a relational database does. On the other side, databases are the most common used persistent storage system and they grant benefits such as security and data integrity but they need to be managed by expert users. The problem is quite significant above all when enterprise or corporate ontologies are used to share infomation…

Data IntegrationOWL OntologyDatabaseSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniSchema MatchingEntity-Relation DiagramHidden Markov Model
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GRAPH-BASED RULES FOR XML DATA CONVERSION TO OWL ONTOLOGY

2010

International audience; The paper presents a flexible method to enrich and populate an existing OWL ontology from XML data based on graph-based rules. These rules are defined in order to populate automatically a new version of an OWL ontology. Today, most of data exchanged between information systems is done with the help of the XML document. Leading researches in the domain of database systems are moving to semantic model in order to store data and its semantics definition. This flexible method consists in populating an existing OWL ontology from XML data. In paper we present such a method based on the definition of a graph which represents rules that drive the populating process.

Ontolog population[INFO.INFO-OH] Computer Science [cs]/Other [cs.OH]ontology enrichment[INFO.INFO-OH]Computer Science [cs]/Other [cs.OH]XML dataComputingMethodologies_DOCUMENTANDTEXTPROCESSING[ INFO.INFO-OH ] Computer Science [cs]/Other [cs.OH]OWL ontologysemantic annotationRDF
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Integration of Spatial processing and knowledge Processing through the Semantic Web Stack

2011

International audience; This paper presents the integration process of spatial technologies and Semantic Web technologies and its associated tool. The result of this work is a spatial query and rule engine of spatial. To do so, existing ontology with spatial elements is adjusted in order to process the spatial knowledge through spatial technologies. This paper outlines the methods and the processes of these adjustments and how results are returned by our tool. The SWRL and the SPARQL language are extended for spatial purpose and the existing OWL ontology wine is used as an application example.

Spatial processing010504 meteorology & atmospheric sciencescomputer.internet_protocolComputer science02 engineering and technologyOntology (information science)computer.software_genre01 natural sciencesSPARQLOWL-SSocial Semantic WebRule languageOWL Ontology0202 electrical engineering electronic engineering information engineeringSPARQL[INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB]Semantic Web StackSemantic WebSWRL0105 earth and related environmental sciencesKnowledge processingInformation retrieval[INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]Databasebusiness.industrySemantic Web Rule Languagecomputer.file_formatSpatial query[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB]020201 artificial intelligence & image processingbusinessQuery languagecomputer
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Graphe-Based Rules For XML Data Conversion to OWL Ontology

2010

International audience; The paper presents a flexible method to enrich and populate an existing OWL ontology from XML data based on graph-based rules. These rules are defined in order to populate automatically a new version of an OWL ontology. Today, most of data exchanged between information systems is done with the help of the XML document. Leading researches in the domain of database systems are moving to semantic model in order to store data and its semantics definition. This flexible method consists in populating an existing OWL ontology from XML data. In paper we present such a method based on the definition of a graph which represents rules that drive the populating process.

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI][INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]ontology enrichment[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB]XML dataComputingMethodologies_DOCUMENTANDTEXTPROCESSING[INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB]Ontology population[ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]OWL ontologysemantic annotation[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]RDF
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A Graph-based Tool for the Translation of XML Data to OWL-DL Ontologies

2011

International audience; Today most of the data exchanged between information systems is done with the help of the XML syntax. Unfortunately when these data have to be integrated, the integration becomes difficult because of the semantics' heterogeneity. Consequently, leading researches in the domain of database systems are moving to semantic model in order to store data and its semantics definition. To benefit from these new systems and technologies, and to integrate different data sources, a flexible method consists in populating an existing OWL ontology from XML data. In paper we present such a method based on the definition of a graph which represents rules that drive the populating proc…

[INFO.INFO-OH] Computer Science [cs]/Other [cs.OH]ontology enrichment[INFO.INFO-OH]Computer Science [cs]/Other [cs.OH]XML data[ INFO.INFO-OH ] Computer Science [cs]/Other [cs.OH]Ontology populationOWL ontologysemantic annotationRDFsemantic annotation.
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