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SimplevisGrid: grid services for visualization of diverse biomedical knowledge and molecular systems data.

Todd H Stokes1, May D Wang

  • 1Electrical and Computer Engineering Department, Georgia Institute of Technology, Atlanta, GA 30332, USA. todd.stokes@bme.gatech.edu

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
|December 8, 2009
PubMed
Summary

SimpleVisGrid standardizes biomedical data visualization formats for cancer research. This improves data sharing and analysis efficiency across research grids.

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Area of Science:

  • Biomedical Informatics
  • Data Visualization
  • Computational Biology

Background:

  • Biomedical data visualization faces challenges due to data scale, complexity, and diversity.
  • Standardizing data formats is crucial, but visualization technology standardization is an emerging area.

Purpose of the Study:

  • To develop and standardize visualization services for biomedical research.
  • To enhance interoperability and efficiency in data analysis within research grids.

Main Methods:

  • SimpleVisGrid extends standard data formats (CSV, PNG, SVG) for grid service inputs/outputs.
  • Four prototype visualizations were developed: data quality, correlation heatmaps, feature landscapes, and network graphs.
  • The system is built on the Cancer Biomedical Informatics Grid (caBIG) common infrastructure.

Main Results:

  • Successfully specified and extended three standard data formats for visualization services.
  • Developed four functional prototype visualizations for diverse biomedical data types.
  • Prepared services and data models for caBIG Silver-level compatibility review and automated workflow integration.

Conclusions:

  • SimpleVisGrid offers tools to aid biomedical communication, discovery, and decision-making.
  • The project encourages further research into standardizing visualization formats.
  • Improved efficiency for large data transfers across research grids is a key outcome.