Name
Abstract | ||
|---|---|---|
Ontologies are widely used in biology and biomedicine for the annotation and integration of data, and hundreds of ontologies have been developed for this purpose. These ontologies also constitute large volumes of formalized domain knowledge, usually expressed in the Web Ontology Language OWL. Computational access to the knowledge contained within them relies on the use of automated reasoning. We have developed Aber-OWL, an ontology repository that provides OWL EL reasoning to answer queries and verify the consistency of ontologies. Aber-OWL also provides a set of web services which provide ontology-based access to scientific literature in Pubmed and Pubmed Central, SPARQL query expansion to retrieve linked data, and integration with Bio2RDF. Here, we report on our experiences with Aber-OWL and outline a roadmap for future development. Aber-OWL is freely available at http://aber-owl.net. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/978-3-319-33245-1_8 | OWLED |
Keywords | Field | DocType |
Biomedical ontology,Semantic web,Literature search,Semantic indexing,Query expansion | Ontology (information science),Data mining,Ontology-based data integration,Information retrieval,Process ontology,Open Biomedical Ontologies,Computer science,OWL-S,Suggested Upper Merged Ontology,Upper ontology,Ontology components,Database | Conference |
Volume | ISSN | Citations |
9557 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 10 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Luke Slater | 1 | 32 | 3.75 |
| Miguel Ángel Rodríguez-García | 2 | 112 | 12.78 |
| Keiron O'Shea | 3 | 0 | 0.34 |
| Paul N. Schofield | 4 | 319 | 25.71 |
| Georgios V. Gkoutos | 5 | 399 | 36.73 |
| Robert Hoehndorf | 6 | 667 | 53.18 |