@inproceedings{
 title = {Linking abstract plans of scientific experiments to their corresponding execution traces},
 type = {inproceedings},
 year = {2019},
 keywords = {Abstractions,Plan,Provenance,Scientific workflows},
 volume = {2526},
 id = {10b04293-1c74-352b-a644-14a983404d17},
 created = {2020-01-21T23:59:00.000Z},
 file_attached = {false},
 profile_id = {a4dd3107-a343-3164-8df4-d46fe9e15cfc},
 last_modified = {2021-03-04T04:10:37.462Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {true},
 abstract = {Copyright © 2019 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). 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 W3C PROV ontology extension and we illustrate our approach with a use case using the WINGS workflow system.},
 bibtype = {inproceedings},
 author = {Markovic, M. and Garijo, D. and Edwards, P.},
 booktitle = {CEUR Workshop Proceedings}
}

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