2017 IEEE International Conference on Web Services (ICWS) (2017)
Honolulu, Hawaii, USA
June 25, 2017 to June 30, 2017
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICWS.2017.21
Workflow is an important way to mashup reusable software services to create value-added data analytics services. Workflow provenance is core to understand how services and workflows behaved in the past, which knowledge can be used to provide a better recommendation. Existing workflow provenance management systems handle various types of provenance separately. A typical data science exploration scenario, however, calls for an integrated view of provenance and seamless transition among different types of provenance. In this paper, a graph-based, uniform provenance model is proposed to link together design-time and run-time provenance, by combining retrospective provenance, prospective provenance, and evolution provenance. Such a unified provenance model will not only facilitate workflow mining and exploration, but also facilitate workflow interoperability. The model is formalized into colored Petri nets for verification and monitoring management. A SQL-like query language is developed, which supports basic queries, recursive queries, and cross-provenance queries. To verify the effectiveness of our model, A web-based, collaborative workflow prototyping system is developed as a proof-of-concept. Experiments have been conducted to evaluate the effectiveness of the proposed SQL-like graph query against SQL query.
Data models, History, Petri nets, Mashups, Interoperability, Database languages, Wheels
X. Duan et al., "Linking Design-Time and Run-Time: A Graph-Based Uniform Workflow Provenance Model," 2017 IEEE International Conference on Web Services (ICWS), Honolulu, Hawaii, USA, 2017, pp. 97-105.