The Semantic Metadatabase (SEMEDA): Ontology Based Integration of Federated Molecular Biological Data Sources.
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| Title: | The Semantic Metadatabase (SEMEDA): Ontology Based Integration of Federated Molecular Biological Data Sources. |
|---|---|
| Authors: | Köhler, Jacob, Schulze-Kremer, Steffen |
| Source: | In Silico Biology. 2002, Vol. 2 Issue 3, p219. 13p. |
| Subjects: | Metadatabases, Bioinformatics |
| Abstract: | A system for "intelligent" semantic integration and querying of federated databases is being implemented by using three main components: A component which enables SQL access to integrated databases by database federation (MARGBench), an ontology based semantic metadatabase (SEMEDA) and an ontology based query interface (SEMEDA-query). In this publication we explain and demonstrate the principles, architecture and the use of SEMEDA. Since SEMEDA is implemented as 3 tiered web application database providers can enter all relevant semantic and technical information about their databases by themselves via a web browser. SEMEDA' s collaborative ontology editing feature is not restricted to database integration, and might also be useful for ongoing ontology developments, such as the "Gene Ontology" [2]. SEMEDA can be found at http://www-bm.cs.uni-magdeburg. de/semeda/. We explain how this ontologically structured information can be used for semantic database integration. In addition, requirements to ontologies for molecular biological database integration are discussed and relevant existing ontologies are evaluated. We further discuss how ontologies and structured knowledge sources can be used in SEMEDA and whether they can be merged supplemented or updated to meet the requirements for semantic database integration. [ABSTRACT FROM AUTHOR] |
| Copyright of In Silico Biology is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 8769696 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: The Semantic Metadatabase (SEMEDA): Ontology Based Integration of Federated Molecular Biological Data Sources. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Köhler%2C+Jacob%22">Köhler, Jacob</searchLink><br /><searchLink fieldCode="AR" term="%22Schulze-Kremer%2C+Steffen%22">Schulze-Kremer, Steffen</searchLink> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22In+Silico+Biology%22">In Silico Biology</searchLink>. 2002, Vol. 2 Issue 3, p219. 13p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Metadatabases%22">Metadatabases</searchLink><br /><searchLink fieldCode="DE" term="%22Bioinformatics%22">Bioinformatics</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: A system for "intelligent" semantic integration and querying of federated databases is being implemented by using three main components: A component which enables SQL access to integrated databases by database federation (MARGBench), an ontology based semantic metadatabase (SEMEDA) and an ontology based query interface (SEMEDA-query). In this publication we explain and demonstrate the principles, architecture and the use of SEMEDA. Since SEMEDA is implemented as 3 tiered web application database providers can enter all relevant semantic and technical information about their databases by themselves via a web browser. SEMEDA' s collaborative ontology editing feature is not restricted to database integration, and might also be useful for ongoing ontology developments, such as the "Gene Ontology" [2]. SEMEDA can be found at http://www-bm.cs.uni-magdeburg. de/semeda/. We explain how this ontologically structured information can be used for semantic database integration. In addition, requirements to ontologies for molecular biological database integration are discussed and relevant existing ontologies are evaluated. We further discuss how ontologies and structured knowledge sources can be used in SEMEDA and whether they can be merged supplemented or updated to meet the requirements for semantic database integration. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of In Silico Biology is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 13 StartPage: 219 Subjects: – SubjectFull: Metadatabases Type: general – SubjectFull: Bioinformatics Type: general Titles: – TitleFull: The Semantic Metadatabase (SEMEDA): Ontology Based Integration of Federated Molecular Biological Data Sources. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Köhler, Jacob – PersonEntity: Name: NameFull: Schulze-Kremer, Steffen IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 09 Text: 2002 Type: published Y: 2002 Identifiers: – Type: issn-print Value: 13866338 Numbering: – Type: volume Value: 2 – Type: issue Value: 3 Titles: – TitleFull: In Silico Biology Type: main |
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