Visual Analytics and Scientific Discoveries

Research Projects

 

          To augment the abilities of scientists and the general public to identify and track the advances and diffusion of scientific knowledge

          To identify salient patterns and trends in massive dynamic domain information from multiple sources and perspectives

 

 

Sponsor

Description

 

 

Title: Coordinated Visualization and Analysis of Sky Survey Data and Astronomical Literature

Program: NSF SEIII

Personnel: Chaomei Chen, IST, Drexel University (PI); Michael Vogeley, Physics, Drexel University (Co-PI)

Partners: NASA Astrophysics Data System (ADS), Thomson ISI

 

The project aims to advance information integration and visualization techniques to facilitate scientific discoveries in astronomy. The research is to develop coordinated visualization, semantic navigation, topic tracking and discovery techniques with direct applications to the use of the Sloan Digital Sky Survey (SDSS) data in astronomical discoveries and the study of its intellectual role in the advancement of astronomical research.

 

 

Title: Northeast Visualization and Analytics Center (NEVAC)

Program: RVAC

Personnel: Alan MacEachren, GeoVISTA, Penn State University (Director, PI); Chaomei Chen, IST, Drexel University (Drexel-PI)

Partners: The Port Authority of New York and New Jersey, GeoDecisions, VideoMining

 

NEVAC is coordinated through Penn State's GeoVISTA Center, and includes collaborators from the Department of Geography, the College of Information Sciences and Technology and the Department of Film-Video and Media Studies, as well as from Drexel University's College of Information Science and Technology in Philadelphia. NEVAC also includes partners from the private and government sectors.

 

Publications:

Chen, C., SanJuan, F. I., SanJuan, E., & Weaver, C. (2006) Visual analysis of conflicting opinions. IEEE Symposium on Visual Analytics Science and Technology (VAST 2006), Baltimore, MA. Oct 31-Nov 2, 2006.

 

 

Title: Predictive Syndromic Surveillance System (PS3)  

Program: United States Army Medical Research

Personnel: Banu Onaral, Drexel University (PI); Chaomei Chen, IST, Drexel University (Co-PI) with Other Co-PIs

 

Fusion and analysis of information sets derived from multiple data sources as a method to improve medical predictive syndromic surveillance systems. PS3 provides a visual display of information stemming from the fusion process that facilitates the efficient use of diverse data streams. Development and integration of three components:

         Advanced patient monitoring and diagnostic system through electronic data collection

         Tumor-tissue image digitization, 2D-image processing, 3D-reconstruction and analysis

         Web-based database management, interactive hierarchical visualization and annotation interface

Potential applications include computer-based infection detection in soft tissue. Integrated tumor prediction system. Research study of the pathogenesis of cancer. Clinical study to assess sensitivity and specificity of radiologic and imaging techniques' effectiveness. Models to create better management and treatment algorithms by allowing prediction of growth patterns based on biopsy histologic findings.

 

Last modified: 8/26/2006