Award Abstract # 0222991
VISUALIZATION: A Metadata-Driven Visualization Interface Technology for Scientific Data Exploration

NSF Org: CCF
Division of Computing and Communication Foundations
Recipient: UNIVERSITY OF CALIFORNIA, DAVIS
Initial Amendment Date: August 30, 2002
Latest Amendment Date: August 18, 2006
Award Number: 0222991
Award Instrument: Continuing Grant
Program Manager: Almadena Chtchelkanova
achtchel@nsf.gov
 (703)292-7498
CCF
 Division of Computing and Communication Foundations
CSE
 Directorate for Computer and Information Science and Engineering
Start Date: September 1, 2002
End Date: March 31, 2007 (Estimated)
Total Intended Award Amount: $0.00
Total Awarded Amount to Date: $265,054.00
Funds Obligated to Date: FY 2002 = $90,428.00
FY 2003 = $86,960.00

FY 2004 = $87,666.00
History of Investigator:
  • Kwan-Liu Ma (Principal Investigator)
    ma@cs.ucdavis.edu
  • Michael Gertz (Co-Principal Investigator)
Recipient Sponsored Research Office: University of California-Davis
1850 RESEARCH PARK DR STE 300
DAVIS
CA  US  95618-6153
(530)754-7700
Sponsor Congressional District: 04
Primary Place of Performance: University of California-Davis
1850 RESEARCH PARK DR STE 300
DAVIS
CA  US  95618-6153
Primary Place of Performance
Congressional District:
04
Unique Entity Identifier (UEI): TX2DAGQPENZ5
Parent UEI:
NSF Program(s): ITR SMALL GRANTS,
ADVANCED COMP RESEARCH PROGRAM,
GRAPHICS & VISUALIZATION
Primary Program Source: app-0102 
app-0103 

app-0104 
Program Reference Code(s): 1652, 9216, HPCC
Program Element Code(s): 168600, 408000, 745300
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.070

ABSTRACT

This project lays out our plan for research and development aimed atdramatically improving the process
and outcome of scientific data analysis and visualization. The improvement will be achieved by coupling an expressive and extensible metadata management framework with novel visualization interfaces that facilitate
effective reuse, sharing, and cross-exploration of visualizationinformation and thus will make a profound
impact on a broad range of scientific applications. The process of scientific visualization is inherently iterative. A good visualization comes from experimenting with visualization and rendering parameters to bring out the most relevant information in the data.
This raises a question. Considering the computer and human time we routinely invest for exploratory and
production visualization, are there methodologies and mechanisms to enhance not only the productivity of
scientists but also their understanding of the visualization process anddata used?
Recent advances in the field of data visualization have been made mainly in rendering and display
technologies (such as realtime volume rendering and immersive environments), but little in coherently managing, representing, and sharing information about the visualization process
and results (images and insights).
Naturally, the various information about data exploration should be shared and reused to leverage
the knowledge and experience scientists gain from visualizing scientific data. A visual representation of the
data exploration process along with expressive models for recording and querying task specific information
help scientists keep track of their visualization experience and findings, use it to generate new visualizations, and share it with others.
While previous research has addressed some related issues, a more comprehensive study remains to be
done. Thus, we propose two complementary avenues of research: (1) new user interfaces for data visualization tasks, and (2) expressive metadata models supporting the recording and
querying of information related to data exploration tasks. In addition, a set of user studies will be
conducted on a Web-based visualization testbed realizing (1) and (2) in order to refine the proposed
methodologies and designs.
Traditional user interfaces cannot support the increasingly complex process of scientific data exploration.
A fundamental change in the conventional designs and functionality must be made to offer more
intuitive interaction, guidance, and enhanced perception. We will begin our study with enriching the graphbased and spreadsheet-like interfaces we have developed, and also investigate alternative designs. An expressive and extensible metadata model representing the data exploration process and its embedded data visualization process is needed. Such a model along with an appropriate user interface makes it possible to manage diverse information about the input and results of the visualization process, analyze parameter coverage and usage, identify unexplored visualization spaces, and incorporate findings on the process and results in form of visualization metadata. The model is independent of the actual visual interface used and is open in that its realization in form of a metadata repository can be loosely coupled with a variety of different visualization tools. A set of interfaces and protocols to the repository will be designed to manage, query, and analyze visualization metadata gathered from and utilized by different visualization tools.
Our goal is ambitious and can only be accomplished by working closely with application scientists.
They will help us understand application-dependent and independent visualization requirements, processes,
and information. In return, we will offer them a new and greatly improved way to understand their scientific
data, which will help them lead to new discoveries quicker, likely with reduced cost.

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