A semantic approach for the requirement-driven discovery of web resources in the Life Sciences

Abstract

Research in the Life Sciences depends on the integration of large, dis- tributed and heterogeneous web resources (e.g. data sources and web services). The discovery of which of these resources are the most appropriate to solve a given task is a complex research question, since there are many candidate resources and there is little, mostly unstructured, metadata to be able to decide among them. In this paper we contribute with a semi-automatic approach, based on semantic techniques, to assist researchers in the discovery of the most appropriate web resources to ful ll a set of requirements. The main feature of our approach is that it exploits broad knowledge resources in order to annotate the unstructured texts that are available in the emerging web-based repositories of web resource metadata. The results show that the web resource discovery process bene ts from a semantic- based approach in several important aspects. One of the advantages is that the user can express her requirements in natural language avoiding the use of speci c vocabularies or query languages. Moreover, the discovery exploits not only the categories or tags of web resources, but also their description and documentation.