Running scientific workflows in distributed and heterogeneous environments has been a motivating approach for provenance management, which is loosely coupled to the workflow execution engine. This kind of approach is interesting because it allows both storage and access to provenance data in a homogeneous way, even in an environment where different workflow management systems work together. However, current approaches overload scientists with many ad hoc tasks, such as script adaptations and implementations of extra functionalities to provide provenance independence. This paper proposes ProvManager, a provenance management approach that eases the gathering, storage, and analysis of provenance information in a distributed and heterogeneous environment scenario, without putting the burden of adaptations on the scientist. ProvManager leverages the provenance management at the experiment level by integrating different workflow executions from multiple workflow management systems.

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Running scientific workflows in distributed environments is motivating the definition of provenance gathering approaches that are loosely coupled to the workflow execution engine. This kind of approach is interesting because it allows both storage and access to provenance data in an integrated way, even in an environment where different workflow systems work together. Therefore, we have proposed a provenance gathering strategy that is independent from the workflow system technology. This strategy has evolved into a provenance management system named ProvManager. In this paper we show how provenance data is captured along in a distributed execution environment with ProvManager and we show its web interface, in which scientists can register experiments, monitor workflow execution, and query provenance data.