| Autor: |
Balcázar, José L., Long, Philip M., Stephan, Frank, Goble, Carole, Corcho, Oscar, Alper, Pinar, Roure, David |
| Zdroj: |
Algorithmic Learning Theory (9783540466499); 2006, p12-12, 1p |
| Abstrakt: |
e-Science is scientific investigation performed through distributed global collaborations between scientists and their resources, and the computing infrastructure that enables this [4]. Scientific progress increasingly depends on pooling know-how and results; making connections between ideas, people, and data; and finding and reusing knowledge and resources generated by others in perhaps unintended ways. It is about harvesting and harnessing the "collective intelligence" of the scientific community. The Semantic Web is an extension of the current Web in which information is given well-defined meaning to facilitate sharing and reuse, better enabling computers and people to work in cooperation [1]. Applying the Semantic Web paradigm to e-Science [3] has the potential to bring significant benefits to scientific discovery [2]. We identify the benefits of lightweight and heavyweight approaches, based on our experiences in the Life Sciences. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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