Unmanaged workflows: Their provenance and use

AKTAŞ M. S., Plale B., Leake D., Mukhi N. K.

Studies in Computational Intelligence, vol.426, pp.59-81, 2013 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Volume: 426
  • Publication Date: 2013
  • Doi Number: 10.1007/978-3-642-29931-5_3
  • Journal Name: Studies in Computational Intelligence
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, zbMATH
  • Page Numbers: pp.59-81
  • Keywords: Case-based reasoning, Data mining, Data provenance, E-Science workflows, Intelligent user interfaces, Provenance capture
  • Yıldız Technical University Affiliated: Yes


Provenance of scientific data will play an increasingly critical role as scientists are encouraged by funding agencies and grand challenge problems to share and preserve scientific data. But it is foolhardy to believe that all human processes, particularly as varied as the scientific discovery process, will be fully automated by a workflow system. Consequently, provenance capture has to be thought of as a problem applied to both human and automated processes. The unmanaged workflow is the full human-driven activity, encompassing tasks whose execution is automated by an orchestration tool, and tasks that are done outside an orchestration tool. In this chapter we discuss the implications of the unmanaged workflow as it affects provenance capture, representation, and use. Illustrations of capture include multiple experiences with unmanaged capture using the Karma tool. Illustrations of use include defining workflows by suggesting additions to workflow designs under construction, reconstructing process traces, and using analysis tools to assess provenance quality. © Springer-Verlag Berlin Heidelberg 2013.