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As users become confronted with a deluge of provenance data, dedicatedtechniques are required to make sense of this kind of information. We presentAggregation by Provenance Types, a provenance graph analysis that is capable ofgenerating provenance graph summaries. It proceeds by converting provenancepaths up to some length k to attributes, referred to as provenance types, andby grouping nodes that have the same provenance types. The summary alsoincludes numeric values representing the frequency of nodes and edges in theoriginal graph. A quantitative evaluation and a complexity analysis show thatthis technique is tractable; with small values of k, it can produce usefulsummaries and can help detect outliers. We illustrate how the generatedsummaries can further be used for conformance checking and visualization.

Aggregation by Provenance Types: A Technique for Summarising Provenance Graphs