A Resourceomic Grid for bioinformatics
Future Generation Computer Systems
Integrating existing scientific workflow systems: the Kepler/Pegasus example
Proceedings of the 2nd workshop on Workflows in support of large-scale science
e-Science and the semantic web: a symbiotic relationship
ALT'06 Proceedings of the 17th international conference on Algorithmic Learning Theory
e-Science and the semantic web: a symbiotic relationship
DS'06 Proceedings of the 9th international conference on Discovery Science
Semantic metadata generation for large scientific workflows
ISWC'06 Proceedings of the 5th international conference on The Semantic Web
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We are familiar with the idea of e-Commerce – the electronic trading between consumers and suppliers. In recent years there has been a commensurate paradigm shift in the way that science is conducted. e-Science is science performed through distributed global collaborations between scientists and their resources enabled by electronic means, in order to solve scientific problems. No one scientific laboratory has the resources or tools, the raw data or derived understanding or the expertise to harness the knowledge available to a scientific community. Real progress depends on pooling know-how and results. It depends on collaboration and making connections between ideas, people, and data. It depends on finding and interpreting results and knowledge generated by scientific colleagues you do not know and who do not know you, to be analysed in ways they did not anticipate, to generate new hypotheses to be pooled in their turn. The importance of e-Science has been highlighted in the UK, for example, by an investment of over £240 million pounds over the past five years to specifically address the research and development issues that have to be tacked to develop a sustainable and effective e-Science e-Infrastructure.