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are now available for many relevant topics (e.g. Gene Ontology, Sequence Ontology,

Phenotype Ontologies etc.), it has not yet been proven what type of resources are

ideally suited for Text Mining solutions.

Investigating on the aims of research in Text Mining and in ontological design, we

find that ontologies are not designed to support Text Mining but rather to improve the

annotation of database content. Although, Text Mining solutions intend to fill databases

with content, it is not the case that Text Mining solution find ontological concepts

easily in the literature, and, even more, ontological resources are not designed

to support Text Mining solutions in the sense that the ontological terms fit to the demands

of a natural language processing system. However, the Text Mining community

exploits ontological resources to link generated evidence from the literature to

the ontological concepts. Furthermore, the ontologies are not only a tool, but also a

target for Text Mining research. Plenty of methods have been devised that automatically

or semi-automatically construct ontologies or enrich existing ontologies by extracting

terms and relationships from biomedical text collections.

These areas are researched by a community of researchers working in a highly interdisciplinary

way in the domains of biology, biochemistry, chemistry, medicine, machine

learning, formal ontologies, natural language processing, bioinformatics and

others. It was the aim for this seminar to bring together researchers from all those

areas to investigate on the state-of-the-art in both research fields, to discuss the suitability

and progress of available resources, to identify areas where we are lacking

tools, standards, or resources, and to foster joint opportunities for Text Mining and

ontological research for the benefits of life science research.

In preparation of the seminar and prior to the meeting, the organizers identified three

areas that best highlight the achievements and challenges in bringing together ontologies,