Visual Analytics for Accelerating Discoveries in Translational Science

Details

• Personal Author:
  Bhavnani SK ; Divekar R ; McMicken V
• Description:
  Translational science increasingly involves the discovery of complex relationships among different granularities of information such as at the molecular, phenotype, and environmental levels. However, few visual analytical systems enable translational researchers to simultaneously represent, and intuitively interact which such complex data. Here we demonstrate a novel system that was designed and implemented by integrating (1) user needs for representing and interacting with complex biomedical data, (2) design heuristics from usability engineering and visual analytics, and (3) agile programming using HTML5 and scalar vector graphics (SVG). A formative evaluation of the system's functionality in two disease datasets demonstrated the efficacy of the system for discovering patterns in data, but required addressing design and performance limitations. [Description provided by NIOSH]
• Subjects:
  Computers Occupational Health Safety
• Keywords:
  Computer Equipment Data Processing Information Processing Translational Research Visual Aids
• Publisher:
  American Medical Informatics Association
• Document Type:
  Text
• Funding:
  Grant
• Genre:
  Abstract or Summary
• Place as Subject:
  OSHA Region 6 ; Texas
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Pages in Document:
  1
• NIOSHTIC Number:
  nn:20055949
• Citation:
  AMIA 2012 Annual Symposium, November 3-7, 2012, Chicago, Illinois. Bethesda, MD: American Medical Informatics Association 2012 Nov; :1
• Federal Fiscal Year:
  2013
• NORA Priority Area:
  Services
• Performing Organization:
  University of Texas Medical Branch, Galveston
• Peer Reviewed:
  False
• Start Date:
  20100901
• Source Full Name:
  AMIA 2012 Annual Symposium, November 3-7, 2012, Chicago, Illinois
• End Date:
  20130131
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:9ec953cfbaad7b79c0bc8987b0995ae674f81d03e159be0acb28268fdc5b9ebf4fbcaa948ce6a1f341234b09ccdac66ab11f4ec3e18407f996992ae98e13414f
• Download URL:
  https://stacks.cdc.gov/view/cdc/213696/cdc_213696_DS1.pdf
• File Type:
  [PDF - 448.30 KB ]