Provenance describes the creation, manipulation and delivery processes of scientific results; and has become a crucial requirement for debugging, understanding, inspecting and reproducing the outcomes of scientific publications. Scientific experiments, in particular computational workflows, often include provenance collection mechanisms that link execution traces to their respective planned specifications. Such provenance traces are typically very fine-grained, and may quickly become too complex or difficult for humans to interpret. In this paper we describe our approach to represent workflow plans and provenance at different levels of abstraction. We describe EP-Plan, a W3CPROV ontology extension and we illustrate our approach with a use case using the WINGS workflow system.
|Title of host publication||Proceedings of the Third International Workshop on Capturing Scientific Knowledge (Sciknow 2019)|
|Number of pages||4|
|Publication status||Accepted/In press - 21 Oct 2019|
|Event||Third International Workshop on Capturing Scientific Knowledge (SciKnow 2019) - Los Angeles, United States|
Duration: 19 Nov 2019 → 19 Nov 2019
|Workshop||Third International Workshop on Capturing Scientific Knowledge (SciKnow 2019)|
|Period||19/11/19 → 19/11/19|
- Scientific workflows
Markovic, M., Garijo, D., & Edwards, P. (Accepted/In press). Linking Abstract Plans of Scientific Experiments to their Corresponding Execution Traces. In Proceedings of the Third International Workshop on Capturing Scientific Knowledge (Sciknow 2019) CEUR-WS.