SEMEDA: ontology based semantic integration of biological databases

Köhler, Jacob; Philippi, Stephan; Lange, Matthias

doi:10.1093/bioinformatics/btg340

Cited by 88 publications

(58 citation statements)

References 26 publications

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“…Although underlined as necessary by [22], the exploitation of both levels had not been implemented for creating biomedical integration systems. In contrast, the hybrid approach is widespread in the artificial intelligence community, mainly for mapping schemas or ontologies [23].…”

Section: Contribution Of the Proposed Methodsmentioning

confidence: 99%

Automatic Methods for Integrating Biomedical Data Sources in a Mediator-Based System

Mougin

Burgun

Bodenreider

et al. 2008

Lecture Notes in Computer Science

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Abstract. The information needed by biologists and physicians for research purposes is distributed over many heterogeneous sources. Integration systems provide a single, centralized and homogeneous interface for users to query multiple information sources simultaneously. The major limitation of integration systems, including mediator-based systems, is that the tasks involved in their creation and maintenance remain mainly manual. To address this limitation, we developed automated methods for facilitating the creation of a mediator-based system. We first implemented an automatic method for acquiring the local schemas of the sources to be integrated. We derived the global schema from the UMLS. Finally, we proposed schema-and instance-based approaches to mapping data elements from the local schemas to the global schema. To illustrate the applicability of our methods, we created a mediator-based system integrating eleven biomedical sources. This prototype is operational, available on the Internet (http://www.med.univ-rennes1.fr/cgi-bin/mougin/These/system.pl) and its evolution is managed semi-automatically.

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Section: Contribution Of the Proposed Methodsmentioning

confidence: 99%

Automatic Methods for Integrating Biomedical Data Sources in a Mediator-Based System

Mougin

Burgun

Bodenreider

et al. 2008

Lecture Notes in Computer Science

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“…This study reveals the inherent difficulties in the integration of vocabularies created in different manners and by specialists in different fields, as well as the strengths of different techniques used to accomplish this integration. J. Kohler, S. Philippi, and M. Lange [24] describe principles and methods used to implement SEMEDA (Semantic Meta Database). Database owners may use SEMEDA to provide semantically integrated access to their databases; they may collaboratively edit and maintain ontologies and controlled vocabularies as well.…”

Section: Ontological Techniques In Medical and Biological Researchmentioning

confidence: 99%

Ontology-based knowledge discovery and sharing in bioinformatics and medical informatics: A brief survey

Huang

Dou

Hayes

et al. 2010

2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery

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Abstract-Worldwide health scientists are producing, accessing, analyzing, integrating, and storing massive amounts of digital medical data daily, through observation, experimentation, and simulation. If we were able to effectively transfer and integrate data from all possible resources, then a deeper understanding of all these data sets and better exposed knowledge, along with appropriate insights and actions, would be granted. Unfortunately, in many cases, the data users are not the data producers, and they thus face challenges in harnessing data in unforeseen and unplanned ways. In order to obtain the ability to integrate heterogeneous data, and thereby efficiently revolutionize the traditional medical and biological research, new methodologies built upon the increasingly pervasive cyberinfrastructure are required to conceptualize traditional medical and biological data, and acquire the "deep" knowledge out of original data thereafter. As formal knowledge representation models, ontologies can render invaluable help in this regard. In this paper, we summarize the state-of-the-art research in ontological techniques and their innovative application in medical and biological areas.

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“…hexose biosynthesis is a monosaccharide biosynthesis [4] hexose biosynthesis is a hexose metabolism,…”

Section: Problems With Is Amentioning

confidence: 99%

“…Semantic heterogeneities at the schema level arise where different names are used for equivalent database fields and tables. Systems to overcome schema level semantic heterogeneities are introduced in [3][4][5][6][7][8]. Semantic heterogeneities arise at the entry level where different terms are used for the same things, or the same terms are used for different things.…”

Section: Introductionmentioning

confidence: 99%

On the Application of Formal Principles to Life Science Data: a Case Study in the Gene Ontology

Smith

Köhler

Kumar³

2004

Lecture Notes in Computer Science

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Abstract. Formal principles governing best practices in classification and definition have for too long been neglected in the construction of biomedical ontologies, in ways which have important negative consequences for data integration and ontology alignment. We argue that the use of such principles in ontology construction can serve as a valuable tool in error-detection and also in supporting reliable manual curation. We argue also that such principles are a prerequisite for the successful application of advanced data integration techniques such as ontology-based multi-database querying, automated ontology alignment and ontology-based text-mining. These theses are illustrated by means of a case study of the Gene Ontology, a project of increasing importance within the field of biomedical data integration.

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SEMEDA: ontology based semantic integration of biological databases

Abstract: SEMEDA is available at http://www-bm.ipk-gatersleben.de/semeda/. Database providers who intend to grant access to their databases via SEMEDA are encouraged to contact the authors.

Cited by 88 publications

References 26 publications

Automatic Methods for Integrating Biomedical Data Sources in a Mediator-Based System

Automatic Methods for Integrating Biomedical Data Sources in a Mediator-Based System

Ontology-based knowledge discovery and sharing in bioinformatics and medical informatics: A brief survey

On the Application of Formal Principles to Life Science Data: a Case Study in the Gene Ontology

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