Support for Cooperative Experiments in e-Science: From Scientific Workflows to Knowledge Sharing

The term e-Science describes computational and data-intensive science. It has become a complementary experiment paradigm alongside the traditional in vivo and in vitro experiment paradigms. e-Science opens new doors for scientists and with it, it exposes a number of challenges such as how to organize huge datasets and coordinate distributed execution. For these challenges, a plethora of technologies and innovations have come together to enable e-Science (Foster and Kesselman 2006). Nowadays, complex scientific experiments designed following the e-Science paradigm are preformed using geographically distributed instruments, data and computing resources. The newly designed scientific experiments are costly, time-consuming, and multidisciplinary. Complex scientific experiments not only require access to geographically distributed hardware and software resources, but also extensive support to foster best practices, dissemination, and re-use