“…These scientific workflows set forward specific challenges in relation to traditional businessoriented workflow management, such as the need to handle large amount of data, intense computational tasks, and more data provenance and "interactive steering" features for scientists and engineers [15]. Furthermore, workflow management technologies have been extensively used to support Collaborative Networks scenarios involving distributed, heterogeneous and autonomous entities [11], [16], [17]. Certainly, other approaches for coordination of these entities are possible, including agent-based technologies, coordination languages, and GRID services.…”