Yin & Yang: Demonstrating complementary provenance from noWorkflow & yesWorkflow

João Felipe Pimentel; Saumen Dey; Timothy McPhillips; Khalid Belhajjame; David Koop; Leonardo Murta; Vanessa Braganholo; Bertram Ludäscher

doi:10.1007/978-3-319-40593-3_13

Yin & Yang: Demonstrating complementary provenance from noWorkflow & yesWorkflow

João Felipe Pimentel, Saumen Dey, Timothy McPhillips, Khalid Belhajjame, David Koop, Leonardo Murta, Vanessa Braganholo, Bertram Ludäscher

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

Abstract

The noWorkflow and YesWorkflow toolkits both enable researchers to capture, store, query, and visualize the provenance of results produced by scripts that process scientific data. noWorkflow captures prospective provenance representing the program structure of Python scripts, and retrospective provenance representing key events observed during script execution. YesWorkflow captures prospective provenance declared through annotations in the comments of scripts, and supports key retrospective provenance queries by observing what files were used or produced by the script. We demonstrate how combining complementary information gathered by noWorkflow and YesWorkflow enables provenance queries and data lineage visualizations neither tool can provide on its own.

Original language	English (US)
Title of host publication	Provenance and Annotation of Data and Processes - 6th International Provenance and Annotation Workshop, IPAW 2016, Proceedings
Editors	Boris Glavic, Marta Mattoso
Publisher	Springer-Verlag Berlin Heidelberg
Pages	161-165
Number of pages	5
ISBN (Print)	9783319405926
DOIs	https://doi.org/10.1007/978-3-319-40593-3_13
State	Published - 2016
Event	6th International Provenance and Annotation Workshop, IPAW 2016 - McLean, United States Duration: Jun 7 2016 → Jun 8 2016

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9672
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	6th International Provenance and Annotation Workshop, IPAW 2016
Country	United States
City	McLean
Period	6/7/16 → 6/8/16

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-319-40593-3_13

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Cite this

Pimentel, J. F., Dey, S., McPhillips, T., Belhajjame, K., Koop, D., Murta, L., Braganholo, V., & Ludäscher, B. (2016). Yin & Yang: Demonstrating complementary provenance from noWorkflow & yesWorkflow. In B. Glavic, & M. Mattoso (Eds.), Provenance and Annotation of Data and Processes - 6th International Provenance and Annotation Workshop, IPAW 2016, Proceedings (pp. 161-165). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9672). Springer-Verlag Berlin Heidelberg. https://doi.org/10.1007/978-3-319-40593-3_13

Yin & Yang : Demonstrating complementary provenance from noWorkflow & yesWorkflow. / Pimentel, João Felipe; Dey, Saumen; McPhillips, Timothy; Belhajjame, Khalid; Koop, David; Murta, Leonardo; Braganholo, Vanessa; Ludäscher, Bertram.

Provenance and Annotation of Data and Processes - 6th International Provenance and Annotation Workshop, IPAW 2016, Proceedings. ed. / Boris Glavic; Marta Mattoso. Springer-Verlag Berlin Heidelberg, 2016. p. 161-165 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9672).

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

Pimentel, JF, Dey, S, McPhillips, T, Belhajjame, K, Koop, D, Murta, L, Braganholo, V & Ludäscher, B 2016, Yin & Yang: Demonstrating complementary provenance from noWorkflow & yesWorkflow. in B Glavic & M Mattoso (eds), Provenance and Annotation of Data and Processes - 6th International Provenance and Annotation Workshop, IPAW 2016, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9672, Springer-Verlag Berlin Heidelberg, pp. 161-165, 6th International Provenance and Annotation Workshop, IPAW 2016, McLean, United States, 6/7/16. https://doi.org/10.1007/978-3-319-40593-3_13

Pimentel JF, Dey S, McPhillips T, Belhajjame K, Koop D, Murta L et al. Yin & Yang: Demonstrating complementary provenance from noWorkflow & yesWorkflow. In Glavic B, Mattoso M, editors, Provenance and Annotation of Data and Processes - 6th International Provenance and Annotation Workshop, IPAW 2016, Proceedings. Springer-Verlag Berlin Heidelberg. 2016. p. 161-165. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-40593-3_13

Pimentel, João Felipe ; Dey, Saumen ; McPhillips, Timothy ; Belhajjame, Khalid ; Koop, David ; Murta, Leonardo ; Braganholo, Vanessa ; Ludäscher, Bertram. / Yin & Yang : Demonstrating complementary provenance from noWorkflow & yesWorkflow. Provenance and Annotation of Data and Processes - 6th International Provenance and Annotation Workshop, IPAW 2016, Proceedings. editor / Boris Glavic ; Marta Mattoso. Springer-Verlag Berlin Heidelberg, 2016. pp. 161-165 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "The noWorkflow and YesWorkflow toolkits both enable researchers to capture, store, query, and visualize the provenance of results produced by scripts that process scientific data. noWorkflow captures prospective provenance representing the program structure of Python scripts, and retrospective provenance representing key events observed during script execution. YesWorkflow captures prospective provenance declared through annotations in the comments of scripts, and supports key retrospective provenance queries by observing what files were used or produced by the script. We demonstrate how combining complementary information gathered by noWorkflow and YesWorkflow enables provenance queries and data lineage visualizations neither tool can provide on its own.",

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