Provenance management for data exploration
DILS'10 Proceedings of the 7th international conference on Data integration in the life sciences
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Provenance is essential in scientific experiments. It contains information that is key to preserving the data, to determining their quality and authorship, and to reproduce as well as validate the results. In complex experiments and analyses, where multiple tools are used to derive data products, provenance captured by these tools must be combined in order to determine the complete lineage of the derived products. In this paper we describe a mediator-based architecture for integrating provenance information from multiple sources. This architecture contains two key components: a global mediated schema that is general and capable of representing provenance information represented in different model; and describe a new system-independent query API that is general and able to express complex queries over provenance information from different sources. We also present a case study where we show how this model was applied to integrate provenance from three provenance-enabled systems and discuss the issues involved in this integration process.