@inproceedings{oliveira_analyzing_2016,
	address = {Washington D.C., USA},
	title = {Analyzing {Provenance} across {Heterogeneous} {Provenance} {Graphs}},
	abstract = {Provenance generated by different workflow systems is generally ex- pressed using different formats. This is not an issue when scientists analyze provenance graphs in isolation, or when they use the same workflow system. However, when analyzing heterogeneous provenance graphs from multiple systems poses a challenge. To address this problem we adopt ProvONE as an integration model, and show how different provenance databases can be con- verted to a global ProvONE schema. Scientists can then query this integrated database, exploring and linking provenance across several different workflows that may represent different implementations of the same experiment. To illus- trate the feasibility of our approach, we developed conceptual mappings be- tween the provenance databases of two workflow systems (e-Science Central and SciCumulus). We provide cartridges that implement these mappings and generate an integrated provenance database expressed as Prolog facts. To demonstrate its usage, we have developed Prolog rules that enable scientists to query the integrated database.},
	booktitle = {Procs. {IPAW} 2016},
	publisher = {Springer},
	author = {Oliveira, Wellington and Missier, Paolo and Ocana, Kary and de Oliveira, Daniel and Braganholo, Vanessa},
	year = {2016},
	keywords = {\#provenance},
}

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