Award Abstract #0513692
Managing Complex Visualizations

NSF Org:	IIS Division of Information & Intelligent Systems
Initial Amendment Date:	July 13, 2005
Latest Amendment Date:	June 10, 2008
Award Number:	0513692
Award Instrument:	Standard Grant
Program Manager:	Sylvia J. Spengler IIS Division of Information & Intelligent Systems CSE Directorate for Computer & Information Science & Engineering
Start Date:	July 15, 2005
Expires:	June 30, 2009 (Estimated)
Awarded Amount to Date:	$530252
Investigator(s):	Juliana Freire juliana@cs.utah.edu (Principal Investigator) Claudio Silva (Co-Principal Investigator)
Sponsor:	University of Utah 75 S 2000 E SALT LAKE CITY, UT 84112 801/581-6903
NSF Program(s):	ITR-INFORMATION INTEGRATION, SCIENCE & ENGINEERING INFORMAT
Field Application(s):	0104000 Information Systems
Program Reference Code(s):	SMET, HPCC, 9251, 9216, 9178
Program Element Code(s):	7373, 7294

ABSTRACT

Scientists are faced with increasingly larger volumes of data to analyze. To analyze and validate various hypotheses, they need to create insightful visual representations of both observed data and simulated processes. Often, insight comes from comparing multiple visualizations. But data exploration through visualization requires scientists to assemble complex pipelines consisting of sequences of operations that transform the data into appropriate visual representations, and today, this process is far from interactive. It contains many error-prone and time-consuming tasks, greatly hindering the scientific discovery process.

The Visualization Management System (VMS) streamlines the creation, execution, and sharing of complex visualization pipelines. It extends traditional dataflow-based visualization systems in several significant directions: it enables interactive multiple-view visualizations by simplifying the creation and maintenance of visualization pipelines, and by optimizing their execution; it provides scalable mechanisms for generating and managing a large number of visualizations; it allows systematic maintenance of data product provenance (akin to a lab notebook) and enables the automatic re-execution of visualization pipelines. VMS gives scientists more control over the visualization process, simplifying many of their day-to-day activities such as allowing them: to resume their explorations where they left off; to apply identical operations to a new data set without having to redo a long sequence of operations; or to share their findings with colleagues.

VMS has the potential to substantially improve scientists' ability to carry out visualization and data exploration. By making VMS freely-available and by integrating it with the leading visualization systems, it can be widely used by the scientific community to support and facilitate scientific discoveries.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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Antonio Baptista, Bill Howe, J. Freire, David Maier, and C. Silva.  "Scientific Exploration in the Era of Ocean Observatories,"  EEE Computing in Science & Engineering,  v.10(3),  2008,  p. 53-58.

C. Scheidegger, D. Koop, E. Santos, H. Vo, S. Callahan, J. Freire, and C. Silva..  "Tackling the Provenance Challenge One Layer at a Time,"  Concurrency and Computation: Practice and Experience,  v.20(5),  2008,  p. 473.

C. Scheidegger, H. Vo, D. Koop, J. Freire, C. Silva.  "Querying and Creating Visualizations by Analogy,"  IEEE Transactions on Visualization and Computer Graphics,  v.13(6),  2007,  p. 1560-1567.

C. Silva, J. Freire, S. Callahan.  "Provenance for Visualizations: Reproducibility and Beyond,"  IEEE Computing in Science & Engineering,  v.9(5),  2008,  p. 82-90.

J. Freire, D. Koop, E. Santos, C. Silva.  "Provenance for Computational Tasks: A Survey,"  IEEE Computing in Science & Engineering,  v.10(3),  2008,  p. 11-21.

S. Davidson, S. Cohen-Boulakia, A. Eyal, B. Ludascher, T. McPhillips, S. Bowers, M. K. Anand, and J. Freire.  "Provenance in Scientific Workflow Systems,"  IEEE Data Engineering Bulletin,  v.32(4),  2007,  p. 44-50.


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