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Meta-Information Visualization to Enhance the Common Operational Picture (MIVEC)

Award Information
Agency: Department of Defense
Branch: Army
Contract: W74V8H-04-P-0434
Agency Tracking Number: A045-002-0105
Amount: $99,998.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: A04-T002
Solicitation Number: N/A
Solicitation Year: 2004
Award Year: 2004
Award Start Date (Proposal Award Date): 2004-08-09
Award End Date (Contract End Date): 2005-02-08
Small Business Information
625 Mount Auburn Street
Cambridge, MA 02138
United States
DUNS: 115243701
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Jonathan Pfautz
 Senior Scientist
 (617) 491-3474
Business Contact
 Paul Gonsalves
Title: Vice President
Phone: (617) 491-3474
Research Institution
 University at Buffalo
 Ann Bisantz
413 Bell Hall, Industrial Engineering Dept.
Buffalo, NY 14260
United States

 (716) 645-2357
 Nonprofit College or University

Decision-making in 21st century warfare environments is characterized by large amounts of complex information from a variety of individual and networked sensor systems that must be rapidly processed by the commander. Part of this complexity is due to meta-information, or, characteristics of information such as uncertainty, staleness, etc. that increase the decision-making burden. Knowledge regarding this meta-information, along with cognitively and perceptually based visualization methods, can be used to relieve the decision-maker's workload and encourage more battlespace-aware decisions. We therefore propose a process for developing Meta-Information Visualizations to Enhance the Common Operation Picture (MIVEC). This process consists of three steps. First, we will perform a cognitive task analysis across a set of case studies to develop a principled categorization of types and sources of information and meta-information, to identify meta-informational requirements, and to identify display elements in existing DoD systems. Second, we will design and prototype a software toolkit for augmenting incoming data with identified meta-information types and for rapidly creating new meta-information visualization methods and interfaces. Third, we will develop an evaluation methodology, including metrics of the effectiveness of each meta-information visualization technique in supporting performance and training. We will demonstrate feasibility of our approach for Phase II development.

* Information listed above is at the time of submission. *

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