
NSF Org: |
CCF Division of Computing and Communication Foundations |
Recipient: |
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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 2003 = $86,960.00 FY 2004 = $87,666.00 |
History of Investigator: |
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Recipient Sponsored Research Office: |
1850 RESEARCH PARK DR STE 300 DAVIS CA US 95618-6153 (530)754-7700 |
Sponsor Congressional District: |
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Primary Place of Performance: |
1850 RESEARCH PARK DR STE 300 DAVIS CA US 95618-6153 |
Primary Place of
Performance Congressional District: |
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Unique Entity Identifier (UEI): |
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Parent UEI: |
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NSF Program(s): |
ITR SMALL GRANTS, ADVANCED COMP RESEARCH PROGRAM, GRAPHICS & VISUALIZATION |
Primary Program Source: |
app-0103 app-0104 |
Program Reference Code(s): |
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Program Element Code(s): |
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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.
Please report errors in award information by writing to: awardsearch@nsf.gov.