Prov viewer: A graph-based visualization tool for interactive exploration of provenance data

Troy Kohwalter; Thiago Oliveira; Juliana Freire; Esteban Clua; Leonardo Murta

doi:10.1007/978-3-319-40593-3_6

Prov viewer: A graph-based visualization tool for interactive exploration of provenance data

Troy Kohwalter, Thiago Oliveira, Juliana Freire, Esteban Clua, Leonardo Murta

Urban Initiative

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

Abstract

The analysis of provenance data for an experiment is often crucial to understand the achieved results. For long-running experiments or when provenance is captured at a low granularity, this analysis process can be overwhelming to the user due to the large volume of provenance data. In this paper we introduce, Prov Viewer, a provenance visualization tool that enables users to interactively explore provenance data. Among the visualization and exploratory features, we can cite zooming, filtering, and coloring. Moreover, we use of other properties such as shape and size to distinguish visual elements. These exploratory features are linked to the provenance semantics to ease the comprehension process. We also introduce collapsing and filtering strategies, allowing different levels of granularity exploration and analysis. We describe case studies that show how Prov Viewer has been successfully used to explore provenance in different domains, including games and urban data.

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
Pages	71-82
Number of pages	12
ISBN (Print)	9783319405926
DOIs	https://doi.org/10.1007/978-3-319-40593-3_6
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/Territory	United States
City	McLean
Period	6/7/16 → 6/8/16

Keywords

Analysis
Graph
Provenance
Tool
Visualization

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-319-40593-3_6

Cite this

Kohwalter, T., Oliveira, T., Freire, J., Clua, E., & Murta, L. (2016). Prov viewer: A graph-based visualization tool for interactive exploration of provenance data. In B. Glavic, & M. Mattoso (Eds.), Provenance and Annotation of Data and Processes - 6th International Provenance and Annotation Workshop, IPAW 2016, Proceedings (pp. 71-82). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9672). Springer Verlag. https://doi.org/10.1007/978-3-319-40593-3_6

Prov viewer: A graph-based visualization tool for interactive exploration of provenance data. / Kohwalter, Troy; Oliveira, Thiago; Freire, Juliana et al.
Provenance and Annotation of Data and Processes - 6th International Provenance and Annotation Workshop, IPAW 2016, Proceedings. ed. / Boris Glavic; Marta Mattoso. Springer Verlag, 2016. p. 71-82 (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

Kohwalter, T, Oliveira, T, Freire, J, Clua, E & Murta, L 2016, Prov viewer: A graph-based visualization tool for interactive exploration of provenance data. 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, pp. 71-82, 6th International Provenance and Annotation Workshop, IPAW 2016, McLean, United States, 6/7/16. https://doi.org/10.1007/978-3-319-40593-3_6

Kohwalter T, Oliveira T, Freire J, Clua E, Murta L. Prov viewer: A graph-based visualization tool for interactive exploration of provenance data. In Glavic B, Mattoso M, editors, Provenance and Annotation of Data and Processes - 6th International Provenance and Annotation Workshop, IPAW 2016, Proceedings. Springer Verlag. 2016. p. 71-82. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-40593-3_6

Kohwalter, Troy ; Oliveira, Thiago ; Freire, Juliana et al. / Prov viewer : A graph-based visualization tool for interactive exploration of provenance data. Provenance and Annotation of Data and Processes - 6th International Provenance and Annotation Workshop, IPAW 2016, Proceedings. editor / Boris Glavic ; Marta Mattoso. Springer Verlag, 2016. pp. 71-82 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{b29bf369ec4a47909999249c2f4b0398,

title = "Prov viewer: A graph-based visualization tool for interactive exploration of provenance data",

abstract = "The analysis of provenance data for an experiment is often crucial to understand the achieved results. For long-running experiments or when provenance is captured at a low granularity, this analysis process can be overwhelming to the user due to the large volume of provenance data. In this paper we introduce, Prov Viewer, a provenance visualization tool that enables users to interactively explore provenance data. Among the visualization and exploratory features, we can cite zooming, filtering, and coloring. Moreover, we use of other properties such as shape and size to distinguish visual elements. These exploratory features are linked to the provenance semantics to ease the comprehension process. We also introduce collapsing and filtering strategies, allowing different levels of granularity exploration and analysis. We describe case studies that show how Prov Viewer has been successfully used to explore provenance in different domains, including games and urban data.",

keywords = "Analysis, Graph, Provenance, Tool, Visualization",

author = "Troy Kohwalter and Thiago Oliveira and Juliana Freire and Esteban Clua and Leonardo Murta",

note = "Funding Information: The authors thank CAPES, CNPq, and FAPERJ for the financial support. Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2016.; 6th International Provenance and Annotation Workshop, IPAW 2016 ; Conference date: 07-06-2016 Through 08-06-2016",

year = "2016",

doi = "10.1007/978-3-319-40593-3_6",

language = "English (US)",

isbn = "9783319405926",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "71--82",

editor = "Boris Glavic and Marta Mattoso",

booktitle = "Provenance and Annotation of Data and Processes - 6th International Provenance and Annotation Workshop, IPAW 2016, Proceedings",

}

TY - GEN

T1 - Prov viewer

T2 - 6th International Provenance and Annotation Workshop, IPAW 2016

AU - Kohwalter, Troy

AU - Oliveira, Thiago

AU - Freire, Juliana

AU - Clua, Esteban

AU - Murta, Leonardo

N1 - Funding Information: The authors thank CAPES, CNPq, and FAPERJ for the financial support. Publisher Copyright: © Springer International Publishing Switzerland 2016.

PY - 2016

Y1 - 2016

N2 - The analysis of provenance data for an experiment is often crucial to understand the achieved results. For long-running experiments or when provenance is captured at a low granularity, this analysis process can be overwhelming to the user due to the large volume of provenance data. In this paper we introduce, Prov Viewer, a provenance visualization tool that enables users to interactively explore provenance data. Among the visualization and exploratory features, we can cite zooming, filtering, and coloring. Moreover, we use of other properties such as shape and size to distinguish visual elements. These exploratory features are linked to the provenance semantics to ease the comprehension process. We also introduce collapsing and filtering strategies, allowing different levels of granularity exploration and analysis. We describe case studies that show how Prov Viewer has been successfully used to explore provenance in different domains, including games and urban data.

AB - The analysis of provenance data for an experiment is often crucial to understand the achieved results. For long-running experiments or when provenance is captured at a low granularity, this analysis process can be overwhelming to the user due to the large volume of provenance data. In this paper we introduce, Prov Viewer, a provenance visualization tool that enables users to interactively explore provenance data. Among the visualization and exploratory features, we can cite zooming, filtering, and coloring. Moreover, we use of other properties such as shape and size to distinguish visual elements. These exploratory features are linked to the provenance semantics to ease the comprehension process. We also introduce collapsing and filtering strategies, allowing different levels of granularity exploration and analysis. We describe case studies that show how Prov Viewer has been successfully used to explore provenance in different domains, including games and urban data.

KW - Analysis

KW - Graph

KW - Provenance

KW - Tool

KW - Visualization

UR - http://www.scopus.com/inward/record.url?scp=84976635982&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84976635982&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-40593-3_6

DO - 10.1007/978-3-319-40593-3_6

M3 - Conference contribution

AN - SCOPUS:84976635982

SN - 9783319405926

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 71

EP - 82

BT - Provenance and Annotation of Data and Processes - 6th International Provenance and Annotation Workshop, IPAW 2016, Proceedings

A2 - Glavic, Boris

A2 - Mattoso, Marta

PB - Springer Verlag

Y2 - 7 June 2016 through 8 June 2016

ER -

Prov viewer: A graph-based visualization tool for interactive exploration of provenance data

Abstract

Publication series

Other

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this