Linking Abstract Plans of Scientific Experiments to their Corresponding Execution Traces

Milan Markovic; Daniel Garijo; Peter Edwards

Linking Abstract Plans of Scientific Experiments to their Corresponding Execution Traces

Milan Markovic, Daniel Garijo, Peter Edwards

Research output: Chapter in Book/Report/Conference proceeding › Published conference contribution

1 Citation (Scopus)

3 Downloads (Pure)

Abstract

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.

Original language	English
Title of host publication	Proceedings of the Third International Workshop on Capturing Scientific Knowledge (Sciknow 2019)
Publisher	CEUR-WS
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

Workshop	Third International Workshop on Capturing Scientific Knowledge (SciKnow 2019)
Country/Territory	United States
City	Los Angeles
Period	19/11/19 → 19/11/19

Keywords

Plan
Scientific workflows
provenance
abstractions

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Markovic, M, Garijo, D & Edwards, P 2019, 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, Third International Workshop on Capturing Scientific Knowledge (SciKnow 2019), Los Angeles, California, United States, 19/11/19. <https://sciknow.github.io/sciknow2019/papers/SciKnow_2019_paper_7.pdf>

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title = "Linking Abstract Plans of Scientific Experiments to their Corresponding Execution Traces",

abstract = "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.",

keywords = "Plan, Scientific workflows, provenance, abstractions",

author = "Milan Markovic and Daniel Garijo and Peter Edwards",

note = "ACKNOWLEDGMENTS The work described in this paper was funded by the award made by the RCUK Digital Economy programme to the University of Aberdeen (EP/N028074/1), a SICSAPECE travel award, the Defense Advanced Research Projects Agency with award W911NF-18-10027, the SIMPLEX program with award W911NF-15-1-0555 and from the National Institutes of Health under awards 1U01CA196387 and 1R01GM117097.; Third International Workshop on Capturing Scientific Knowledge (SciKnow 2019) ; Conference date: 19-11-2019 Through 19-11-2019",

year = "2019",

month = oct,

day = "21",

language = "English",

booktitle = "Proceedings of the Third International Workshop on Capturing Scientific Knowledge (Sciknow 2019)",

publisher = "CEUR-WS",

}

TY - GEN

T1 - Linking Abstract Plans of Scientific Experiments to their Corresponding Execution Traces

AU - Markovic, Milan

AU - Garijo, Daniel

AU - Edwards, Peter

N1 - ACKNOWLEDGMENTS The work described in this paper was funded by the award made by the RCUK Digital Economy programme to the University of Aberdeen (EP/N028074/1), a SICSAPECE travel award, the Defense Advanced Research Projects Agency with award W911NF-18-10027, the SIMPLEX program with award W911NF-15-1-0555 and from the National Institutes of Health under awards 1U01CA196387 and 1R01GM117097.

PY - 2019/10/21

Y1 - 2019/10/21

N2 - 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.

AB - 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.

KW - Plan

KW - Scientific workflows

KW - provenance

KW - abstractions

M3 - Published conference contribution

BT - Proceedings of the Third International Workshop on Capturing Scientific Knowledge (Sciknow 2019)

PB - CEUR-WS

T2 - Third International Workshop on Capturing Scientific Knowledge (SciKnow 2019)

Y2 - 19 November 2019 through 19 November 2019

ER -

Linking Abstract Plans of Scientific Experiments to their Corresponding Execution Traces

Abstract

Workshop

Keywords

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