Lexical Characterization and Analysis of the BioPortal Ontologies View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2013

AUTHORS

Manuel Quesada-Martínez , Jesualdo Tomás Fernández-Breis , Robert Stevens

ABSTRACT

The increasing interest of the biomedical community in ontologies can be exemplified by the availability of hundreds of biomedical ontologies and controlled vocabularies, and by the international recommendations and efforts that suggest ontologies should play a critical role in the achievement of semantic interoperability in healthcare. However, many of the available biomedical ontologies are rich in human understandable labels, but are less rich in machine processable axioms, so their effectiveness for supporting advanced data analysis processes is limited. In this context, developing methods for analysing the labels and deriving axioms from them would contribute to make biomedical ontologies more useful. In fact, our recent work revealed that exploiting the regularities and structure of the labels could contribute to that axiomatic enrichment.In this paper, we present an approach for analysing and characterising biomedical ontologies from a lexical perspective, that is, by analysing the structure and content of the labels. This study has several goals: (1) characterization of the ontologies by the patterns found in their labels; (2) identifying which ones would be more appropriate for applying enrichment processes based on the labels; (3) inspecting how ontology re-use is being addressed for patterns found in more than one ontology.Our analysis method has been applied to BioPortal, which is likely to be the most popular repository of biomedical ontologies, containing more than two hundred resources. We have found that there is a high redundancy in the labels of the ontologies; it would be interesting to exploit the content and structure of the labels of many of them and that it seems that re-use is not always performed as it should be. More... »

PAGES

206-215

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-38326-7_31

DOI

http://dx.doi.org/10.1007/978-3-642-38326-7_31

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1020446402


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