Abstract

Data-intensive workflows process and produce large volumes of data. The volume of data, number of workflow participants and activities may range from small to large numbers. The traditional way of logging experimental process is no longer valid. This has resulted in a need for techniques to automatically collect information on workflows known as provenance. Several solutions for e-Science provenance have been proposed but these are predominantly domain and application specific. In this chapter, the requirements of e-Science provenance systems are first clearly defined, and then a novel solution named the Vienna e-Science Provenance System (VePS) that satisfies these requirements is proposed. The VePS not only promises to be light weight, workflow enactment engine, domain and application independent, but it also measures the significance of workflow parameters using the Ant Colony Optimization meta-heuristic technique. Major contributions include: (1) interoperable provenance system, (2) quantification of parameters significance, and (3) generation of executable workflow documents.

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