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

TL;DR

This paper presents a semantic, semi-automatic method to help Life Sciences researchers discover the most suitable web services from large, heterogeneous data sources based on specific requirements.

Contribution

It introduces a novel semantic approach that automates the discovery process of web services tailored to research needs in Life Sciences.

Findings

Improves accuracy of web service discovery in Life Sciences

Reduces manual effort in selecting appropriate web services

Enhances integration of heterogeneous data sources

Abstract

Research in the Life Sciences depends on the integration of large, distributed and heterogeneous 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 is a large amount of plausible candidates and there is little, mostly unstructured, metadata to be able to decide among them.We contribute a semi-automatic approach,based on semantic techniques, to assist researchers in the discovery of the most appropriate web services to full a set of given requirements.