A Semantic Workflow Mechanism to Realise Experimental Goals and Constraints

Edoardo Pignotti; Peter Edwards; Gary Polhill; Nick Gotts; Alun Preece

doi:http://dx.doi.org/10.1109/WORKS.2008.4723962

A Semantic Workflow Mechanism to Realise Experimental Goals and Constraints

Edoardo Pignotti^*, Peter Edwards, Gary Polhill, Nick Gotts, Alun Preece

^*Corresponding author for this work

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

Abstract

Workflow technologies provide scientific researchers with a flexible problem-solving environment, by facilitating the creation and execution of experiments from a pool of available services. In this paper we argue that in order to better characterise such experiments we need to go beyond low-level service composition and execution details by capturing higher-level descriptions of the scientific process. Current workflow technologies do not incorporate any representation of such experimental constraints and goals, which we refer to as the scientist's intent. We have developed a framework based upon use of a number of Semantic Web technologies, including the OWL ontology language and the Semantic Web Rule Language (SWRL), to capture scientist's intent. Through the use of a social simulation case study we illustrate the benefits of using this framework in terms of workflow monitoring, workflow provenance and enrichment of experimental results.

Original language	English
Title of host publication	2008 Third Workshop on Workflows in Support of Large-Scale Science (WORKS 2008)
Publisher	IEEE Explore
Pages	76
Number of pages	3
ISBN (Print)	978-1-4244-2827-4
DOIs	https://doi.org/10.1109/WORKS.2008.4723962
Publication status	Published - 2008
Event	3rd Workshop on Workflows in Support of Large-Scale Science - Austin Duration: 17 Nov 2008 → …

Conference

Conference	3rd Workshop on Workflows in Support of Large-Scale Science
City	Austin
Period	17/11/08 → …

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Cite this

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title = "A Semantic Workflow Mechanism to Realise Experimental Goals and Constraints",

abstract = "Workflow technologies provide scientific researchers with a flexible problem-solving environment, by facilitating the creation and execution of experiments from a pool of available services. In this paper we argue that in order to better characterise such experiments we need to go beyond low-level service composition and execution details by capturing higher-level descriptions of the scientific process. Current workflow technologies do not incorporate any representation of such experimental constraints and goals, which we refer to as the scientist's intent. We have developed a framework based upon use of a number of Semantic Web technologies, including the OWL ontology language and the Semantic Web Rule Language (SWRL), to capture scientist's intent. Through the use of a social simulation case study we illustrate the benefits of using this framework in terms of workflow monitoring, workflow provenance and enrichment of experimental results.",

author = "Edoardo Pignotti and Peter Edwards and Gary Polhill and Nick Gotts and Alun Preece",

year = "2008",

doi = "http://dx.doi.org/10.1109/WORKS.2008.4723962",

language = "English",

isbn = "978-1-4244-2827-4",

pages = "76",

booktitle = "2008 Third Workshop on Workflows in Support of Large-Scale Science (WORKS 2008)",

publisher = "IEEE Explore",

note = "3rd Workshop on Workflows in Support of Large-Scale Science ; Conference date: 17-11-2008",

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T1 - A Semantic Workflow Mechanism to Realise Experimental Goals and Constraints

AU - Pignotti, Edoardo

AU - Edwards, Peter

AU - Polhill, Gary

AU - Gotts, Nick

AU - Preece, Alun

PY - 2008

Y1 - 2008

N2 - Workflow technologies provide scientific researchers with a flexible problem-solving environment, by facilitating the creation and execution of experiments from a pool of available services. In this paper we argue that in order to better characterise such experiments we need to go beyond low-level service composition and execution details by capturing higher-level descriptions of the scientific process. Current workflow technologies do not incorporate any representation of such experimental constraints and goals, which we refer to as the scientist's intent. We have developed a framework based upon use of a number of Semantic Web technologies, including the OWL ontology language and the Semantic Web Rule Language (SWRL), to capture scientist's intent. Through the use of a social simulation case study we illustrate the benefits of using this framework in terms of workflow monitoring, workflow provenance and enrichment of experimental results.

AB - Workflow technologies provide scientific researchers with a flexible problem-solving environment, by facilitating the creation and execution of experiments from a pool of available services. In this paper we argue that in order to better characterise such experiments we need to go beyond low-level service composition and execution details by capturing higher-level descriptions of the scientific process. Current workflow technologies do not incorporate any representation of such experimental constraints and goals, which we refer to as the scientist's intent. We have developed a framework based upon use of a number of Semantic Web technologies, including the OWL ontology language and the Semantic Web Rule Language (SWRL), to capture scientist's intent. Through the use of a social simulation case study we illustrate the benefits of using this framework in terms of workflow monitoring, workflow provenance and enrichment of experimental results.

U2 - http://dx.doi.org/10.1109/WORKS.2008.4723962

DO - http://dx.doi.org/10.1109/WORKS.2008.4723962

M3 - Published conference contribution

SN - 978-1-4244-2827-4

SP - 76

BT - 2008 Third Workshop on Workflows in Support of Large-Scale Science (WORKS 2008)

PB - IEEE Explore

T2 - 3rd Workshop on Workflows in Support of Large-Scale Science

Y2 - 17 November 2008

ER -

A Semantic Workflow Mechanism to Realise Experimental Goals and Constraints

Abstract

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