ausblenden:
Schlagwörter:
Knowledge Networking; e-Science
Zusammenfassung:
Up until now, crucial life science information resources, whether bibliographic
or factual databases, are isolated from each other. Moreover,
semantic metadata intended to structure their contents is supplied in
a manual form only. In the StemNet project we aim at developing a
framework for semantic interoperability for these resources. This will
facilitate the extraction of relevant information from textual sources
and the generation of semantic metadata in a fully automatic manner.
In this way, (from a computational perspective) unstructured life science
documents are linked to structured biological fact databases, in
particular to the identifiers of genes, proteins, etc. Thus, life scientists
will be able to seamlessly access information from a homogeneous
platform, despite the fact that the original information was unlinked
and scattered over the whole variety of heterogeneous life science information
resources and, therefore, almost inaccessible for integrated
systematic search by academic, clinical, or industrial users.
