SCHEDULE: NOV 10-16, 2012
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Visualizing Large Scale Scientific Data Provenance
SESSION: Research Poster Reception
EVENT TYPE: Posters and Electronic Posters
TIME: 5:15PM - 7:00PM
SESSION CHAIR: Torsten Hoefler
AUTHOR(S):Peng Chen, Beth Plale
ROOM:East Entrance
ABSTRACT:
Visualization increases the understanding of scientific data by facilitating exploration and explanation of the data. Provenance contributes to data understanding by exposing contributing factors that went in to producing a particular research result. However, provenance of scientific data can grow voluminous quickly because of the large amount of (intermediate) data and ever-increasing complexity. While previous research on visualizing provenance data focuses on small to medium sized provenance data, we develop visualization techniques for exploration and explanation of large scale provenance, including layout algorithm, visual style, graph abstraction techniques, graph matching algorithm, and temporal representation technique to deal with the high complexity.
Chair/Author Details:
Torsten Hoefler (Chair) - ETH Zurich
Peng Chen - Indiana University
Beth Plale - Indiana University
Click here to download .ics calendar file
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Visualizing Large Scale Scientific Data Provenance
SESSION: Research Poster Reception
EVENT TYPE:
TIME: 5:15PM - 7:00PM
SESSION CHAIR: Torsten Hoefler
AUTHOR(S):Peng Chen, Beth Plale
ROOM:East Entrance
ABSTRACT:
Visualization increases the understanding of scientific data by facilitating exploration and explanation of the data. Provenance contributes to data understanding by exposing contributing factors that went in to producing a particular research result. However, provenance of scientific data can grow voluminous quickly because of the large amount of (intermediate) data and ever-increasing complexity. While previous research on visualizing provenance data focuses on small to medium sized provenance data, we develop visualization techniques for exploration and explanation of large scale provenance, including layout algorithm, visual style, graph abstraction techniques, graph matching algorithm, and temporal representation technique to deal with the high complexity.
Chair/Author Details:
Torsten Hoefler (Chair) - ETH Zurich
Peng Chen - Indiana University
Beth Plale - Indiana University
Click here to download .ics calendar file