SC12 Home > SC12 Schedule > SC12 Presentation - Visualizing Large Scale Scientific Data Provenance

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

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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

Add to iCal  Click here to download .ics calendar file

Add to Outlook  Click here to download .vcs calendar file

Add to Google Calendarss  Click here to add event to your Google Calendar