KA-SB: from data integration to large scale reasoning
<p>Abstract</p> <p>Background</p> <p>The analysis of information in the biological domain is usually focused on the analysis of data from single on-line data sources. Unfortunately, studying a biological process requires having access to disperse, heterogeneous, autonom...
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doaj-d75043232d5c44deb8d56dc672af81062020-11-25T01:35:10ZengBMCBMC Bioinformatics1471-21052009-10-0110Suppl 10S510.1186/1471-2105-10-S10-S5KA-SB: from data integration to large scale reasoningAldana-Montes José FMolina-Castro JoaquínChniber OthmaneKerzazi AmineNavas-Delgado IsmaelRoldán-García María del Mar<p>Abstract</p> <p>Background</p> <p>The analysis of information in the biological domain is usually focused on the analysis of data from single on-line data sources. Unfortunately, studying a biological process requires having access to disperse, heterogeneous, autonomous data sources. In this context, an analysis of the information is not possible without the integration of such data.</p> <p>Methods</p> <p>KA-SB is a querying and analysis system for final users based on combining a data integration solution with a reasoner. Thus, the tool has been created with a process divided into two steps: 1) KOMF, the Khaos Ontology-based Mediator Framework, is used to retrieve information from heterogeneous and distributed databases; 2) the integrated information is crystallized in a (persistent and high performance) reasoner (DBOWL). This information could be further analyzed later (by means of querying and reasoning).</p> <p>Results</p> <p>In this paper we present a novel system that combines the use of a mediation system with the reasoning capabilities of a large scale reasoner to provide a way of finding new knowledge and of analyzing the integrated information from different databases, which is retrieved as a set of ontology instances. This tool uses a graphical query interface to build user queries easily, which shows a graphical representation of the ontology and allows users o build queries by clicking on the ontology concepts.</p> <p>Conclusion</p> <p>These kinds of systems (based on KOMF) will provide users with very large amounts of information (interpreted as ontology instances once retrieved), which cannot be managed using traditional main memory-based reasoners. We propose a process for creating persistent and scalable knowledgebases from sets of OWL instances obtained by integrating heterogeneous data sources with KOMF. This process has been applied to develop a demo tool <url>http://khaos.uma.es/KA-SB</url>, which uses the BioPax Level 3 ontology as the integration schema, and integrates UNIPROT, KEGG, CHEBI, BRENDA and SABIORK databases.</p> |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Aldana-Montes José F Molina-Castro Joaquín Chniber Othmane Kerzazi Amine Navas-Delgado Ismael Roldán-García María del Mar |
spellingShingle |
Aldana-Montes José F Molina-Castro Joaquín Chniber Othmane Kerzazi Amine Navas-Delgado Ismael Roldán-García María del Mar KA-SB: from data integration to large scale reasoning BMC Bioinformatics |
author_facet |
Aldana-Montes José F Molina-Castro Joaquín Chniber Othmane Kerzazi Amine Navas-Delgado Ismael Roldán-García María del Mar |
author_sort |
Aldana-Montes José F |
title |
KA-SB: from data integration to large scale reasoning |
title_short |
KA-SB: from data integration to large scale reasoning |
title_full |
KA-SB: from data integration to large scale reasoning |
title_fullStr |
KA-SB: from data integration to large scale reasoning |
title_full_unstemmed |
KA-SB: from data integration to large scale reasoning |
title_sort |
ka-sb: from data integration to large scale reasoning |
publisher |
BMC |
series |
BMC Bioinformatics |
issn |
1471-2105 |
publishDate |
2009-10-01 |
description |
<p>Abstract</p> <p>Background</p> <p>The analysis of information in the biological domain is usually focused on the analysis of data from single on-line data sources. Unfortunately, studying a biological process requires having access to disperse, heterogeneous, autonomous data sources. In this context, an analysis of the information is not possible without the integration of such data.</p> <p>Methods</p> <p>KA-SB is a querying and analysis system for final users based on combining a data integration solution with a reasoner. Thus, the tool has been created with a process divided into two steps: 1) KOMF, the Khaos Ontology-based Mediator Framework, is used to retrieve information from heterogeneous and distributed databases; 2) the integrated information is crystallized in a (persistent and high performance) reasoner (DBOWL). This information could be further analyzed later (by means of querying and reasoning).</p> <p>Results</p> <p>In this paper we present a novel system that combines the use of a mediation system with the reasoning capabilities of a large scale reasoner to provide a way of finding new knowledge and of analyzing the integrated information from different databases, which is retrieved as a set of ontology instances. This tool uses a graphical query interface to build user queries easily, which shows a graphical representation of the ontology and allows users o build queries by clicking on the ontology concepts.</p> <p>Conclusion</p> <p>These kinds of systems (based on KOMF) will provide users with very large amounts of information (interpreted as ontology instances once retrieved), which cannot be managed using traditional main memory-based reasoners. We propose a process for creating persistent and scalable knowledgebases from sets of OWL instances obtained by integrating heterogeneous data sources with KOMF. This process has been applied to develop a demo tool <url>http://khaos.uma.es/KA-SB</url>, which uses the BioPax Level 3 ontology as the integration schema, and integrates UNIPROT, KEGG, CHEBI, BRENDA and SABIORK databases.</p> |
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