DistillFlow: Removing redundancy in scientific workflows

Jiuqiang Chen; Carole Goble; Sarah Cohen-Boulakia; Paolo Missier; Christine Froidevaux; Alan R. Williams

doi:10.1145/2618243.2618287

DistillFlow: Removing redundancy in scientific workflows

Jiuqiang Chen, Carole Goble, Sarah Cohen-Boulakia, Paolo Missier, Christine Froidevaux, Alan R. Williams

Computer Science

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

Abstract

Scientific workflows management systems are increasingly used by scientists to specify complex data processing pipelines. Workflows are represented using a graph structure, where nodes represent tasks and links represent the dataflow. However, the complexity of workflow structures is increasing over time, reducing the rate of scientific workflows reuse. Here, we introduce DistillFlow, a tool based on effective methods for workflow design, with a focus on the Taverna model. DistillFlow is able to detect "anti-patterns" in the structure of workflows (idiomatic forms that lead to over-complicated design) and replace them with different patterns to reduce the workflow's overall structural complexity. Rewriting workflows in this way is beneficial both in terms of user experience and workflow maintenance.

Original language	English
Title of host publication	SSDBM 2014 - Proceedings of the 26th International Conference on Scientific and Statistical Database Management
Publisher	Association for Computing Machinery
ISBN (Print)	9781450327220
DOIs	https://doi.org/10.1145/2618243.2618287
Publication status	Published - 2014
Event	26th International Conference on Scientific and Statistical Database Management, SSDBM 2014 - Aalborg, Denmark Duration: 30 Jun 2014 → 2 Jul 2014

Publication series

Name	ACM International Conference Proceeding Series

Conference

Conference	26th International Conference on Scientific and Statistical Database Management, SSDBM 2014
Country/Territory	Denmark
City	Aalborg
Period	30/06/14 → 2/07/14

ASJC Scopus subject areas

Software
Human-Computer Interaction
Computer Vision and Pattern Recognition
Computer Networks and Communications

Access to Document

10.1145/2618243.2618287

Cite this

Chen, J., Goble, C., Cohen-Boulakia, S., Missier, P., Froidevaux, C., & Williams, A. R. (2014). DistillFlow: Removing redundancy in scientific workflows. In SSDBM 2014 - Proceedings of the 26th International Conference on Scientific and Statistical Database Management Article 46 (ACM International Conference Proceeding Series). Association for Computing Machinery . https://doi.org/10.1145/2618243.2618287

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title = "DistillFlow: Removing redundancy in scientific workflows",

abstract = "Scientific workflows management systems are increasingly used by scientists to specify complex data processing pipelines. Workflows are represented using a graph structure, where nodes represent tasks and links represent the dataflow. However, the complexity of workflow structures is increasing over time, reducing the rate of scientific workflows reuse. Here, we introduce DistillFlow, a tool based on effective methods for workflow design, with a focus on the Taverna model. DistillFlow is able to detect {"}anti-patterns{"} in the structure of workflows (idiomatic forms that lead to over-complicated design) and replace them with different patterns to reduce the workflow's overall structural complexity. Rewriting workflows in this way is beneficial both in terms of user experience and workflow maintenance.",

author = "Jiuqiang Chen and Carole Goble and Sarah Cohen-Boulakia and Paolo Missier and Christine Froidevaux and Williams, {Alan R.}",

year = "2014",

doi = "10.1145/2618243.2618287",

language = "English",

isbn = "9781450327220",

series = "ACM International Conference Proceeding Series",

publisher = "Association for Computing Machinery ",

booktitle = "SSDBM 2014 - Proceedings of the 26th International Conference on Scientific and Statistical Database Management",

note = "26th International Conference on Scientific and Statistical Database Management, SSDBM 2014 ; Conference date: 30-06-2014 Through 02-07-2014",

}

Chen, J, Goble, C, Cohen-Boulakia, S, Missier, P, Froidevaux, C & Williams, AR 2014, DistillFlow: Removing redundancy in scientific workflows. in SSDBM 2014 - Proceedings of the 26th International Conference on Scientific and Statistical Database Management., 46, ACM International Conference Proceeding Series, Association for Computing Machinery , 26th International Conference on Scientific and Statistical Database Management, SSDBM 2014, Aalborg, Denmark, 30/06/14. https://doi.org/10.1145/2618243.2618287

DistillFlow: Removing redundancy in scientific workflows. / Chen, Jiuqiang; Goble, Carole; Cohen-Boulakia, Sarah et al.
SSDBM 2014 - Proceedings of the 26th International Conference on Scientific and Statistical Database Management. Association for Computing Machinery , 2014. 46 (ACM International Conference Proceeding Series).

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

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T2 - 26th International Conference on Scientific and Statistical Database Management, SSDBM 2014

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AU - Goble, Carole

AU - Cohen-Boulakia, Sarah

AU - Missier, Paolo

AU - Froidevaux, Christine

AU - Williams, Alan R.

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AB - Scientific workflows management systems are increasingly used by scientists to specify complex data processing pipelines. Workflows are represented using a graph structure, where nodes represent tasks and links represent the dataflow. However, the complexity of workflow structures is increasing over time, reducing the rate of scientific workflows reuse. Here, we introduce DistillFlow, a tool based on effective methods for workflow design, with a focus on the Taverna model. DistillFlow is able to detect "anti-patterns" in the structure of workflows (idiomatic forms that lead to over-complicated design) and replace them with different patterns to reduce the workflow's overall structural complexity. Rewriting workflows in this way is beneficial both in terms of user experience and workflow maintenance.

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M3 - Conference contribution

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T3 - ACM International Conference Proceeding Series

BT - SSDBM 2014 - Proceedings of the 26th International Conference on Scientific and Statistical Database Management

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ER -

Chen J, Goble C, Cohen-Boulakia S, Missier P, Froidevaux C, Williams AR. DistillFlow: Removing redundancy in scientific workflows. In SSDBM 2014 - Proceedings of the 26th International Conference on Scientific and Statistical Database Management. Association for Computing Machinery . 2014. 46. (ACM International Conference Proceeding Series). doi: 10.1145/2618243.2618287

DistillFlow: Removing redundancy in scientific workflows

Abstract

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ASJC Scopus subject areas

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