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

• Published in: Knowledge and information systems Vol. 34; no. 3; pp. 671 - 690
• Main Authors: Pérez-Catalán, María, Berlanga, Rafael, Sanz, Ismael, Aramburu, María José
• Format: Journal Article
• Language: English
• Published: London Springer-Verlag 01.03.2013; Springer; Springer Nature B.V
• Subjects: Analysis; Applied sciences; Artificial intelligence; Biologists; Biology; Categories; Computer Science; Computer science; control theory; systems; Computer systems and distributed systems. User interface; Data Mining and Knowledge Discovery; Database Management; Exact sciences and technology; Information Storage and Retrieval; Information systems; Information Systems and Communication Service; Information Systems Applications (incl.Internet); Information systems. Data bases; IT in Business; Laboratories; Life sciences; Memory organisation. Data processing; Metadata; Online information services; Ontology; Regular Paper; Semantic web; Semantics; Software; Speech and sound recognition and synthesis. Linguistics; Studies; Tags; Tasks; Texts; Vocabularies & taxonomies; Life Sciences; Web resources discovery; Requirements-driven methods; Knowledge resources; Vocabulary; Query language; Semantic analysis; Documentation; Web service; Metadata; Text; Distributed computing; Semantics; World wide web; User requirement; Knowledge discovery; Publish subscribe middleware; Natural language; Internet; Resource management; Service oriented; User need
• ISSN: 0219-1377; 0219-3116
• DOI: 10.1007/s10115-012-0498-5

Research in the Life Sciences depends on the integration of large, distributed 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 to a semi-automatic approach, based on semantic techniques, to assist researchers in the discovery of the most appropriate web resources to fulfill 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 benefits 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 specific vocabularies or query languages. Moreover, the discovery exploits not only the categories or tags of web resources, but also their description and documentation.