Abstract
The life sciences are a promising application area for semantic web technologies as there are large online structured and unstructured data repositories and ontologies, which structure this knowledge. We briefly give an overview over biomedical ontologies and show how they can help to locate, retrieve, and integrate biomedical data. Annotating literature with ontology terms is an important problem to support such ontology-based searches. We review the steps involved in this text mining task and introduce the ontology-based search engine GoPubMed. As the underlying data sources evolve, so do the ontologies. We give a brief overview over different approaches supporting the semi-automatic evolution of ontologies.

URL:
http://rewerse.net/publications/rewerse-publications.html#REWERSE-RP-2006-057

BibTeX:

@inproceedings{REWERSE-RP-2006-057,
	author = {Andreas Doms and Vaida Jakoniene and Patrick Lambrix and Michael Schroeder and Thomas W\"achter},
	title = {Ontologies and Text Mining as a Basis for a Semantic Web for the Life Sciences},
	booktitle = {Proceedings of Summer School Reasoning Web 2006, Lisbon, Portugal (4th--8th September 2006)},
	year = {2006},
	volume = {4126},
	organization = {REWERSE},
	series = {LNCS},
	pages = {164--183},
	url = {http://rewerse.net/publications/rewerse-publications.html#REWERSE-RP-2006-057}
}