Towards Modeling and Reasoning Support for Early-Phase Requirements Engineering
RE '97 Proceedings of the 3rd IEEE International Symposium on Requirements Engineering
Modelling strategic relationships for process reengineering
Modelling strategic relationships for process reengineering
Intelligent client for integrating bioinformatics services
Bioinformatics
The myGrid ontology: bioinformatics service discovery
International Journal of Bioinformatics Research and Applications
Measure Selection in Multi-similarity XML Applications
DEXA '08 Proceedings of the 2008 19th International Conference on Database and Expert Systems Application
Requirements gathering in a model-based approach for the design of multi-similarity systems
Proceedings of the first international workshop on Model driven service engineering and data quality and security
A string metric for ontology alignment
ISWC'05 Proceedings of the 4th international conference on The Semantic Web
MoDELS'05 Proceedings of the 2005 international conference on Satellite Events at the MoDELS
A survey of automated web service composition methods
SWSWPC'04 Proceedings of the First international conference on Semantic Web Services and Web Process Composition
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Current research in domains such as the Life Sciences depends heavily on the integration of information coming from diverse sources, which are typically highly complex and heterogeneous, and usually require exploratory access. Web services are increasingly used as the preferred method for accessing and processing these sources. Due to the large number of available web services, the sheer complexity of the data and the frequent lack of documentation, discovering the most appropriate web service for a given task is a challenge for the user. In this paper we propose a semi-automatic approach to assist the user in the discovery of which web services are the most appropriate to achieve her requirements. We describe the overall framework of our approach and we provide a detailed description of the techniques used in each phase of our approach. Finally, the usefulness of our approach is demonstrated through a Bioinformatics case study.