Lauro Lins, David Koop, Erik W. Anderson, Steven P. Callahan, Emanuele Santos, Carlos E. Scheidegger, Juliana Freire, Claudio T. Silva. SSDBM 2008.

As provenance-enabled systems are deployed, and increasing volumes of provenance information are collected, there is a unique opportunity to leverage and obtain useful knowledge from this data. In this paper, we take a first step at analyzing this data. We present a preliminary analysis of workflow evolution provenance generated by thirty subjects who worked on six distinct exploratory tasks over the period of four months. This initial analysis shows that useful statistics can be extracted from this data that provide insights into how different people interact with workflow systems to solve problems.

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