• Corpus ID: 59626240

Visualization and Integrated Data Mining of Disparate Information

@inproceedings{Saffer2001VisualizationAI,
  title={Visualization and Integrated Data Mining of Disparate Information},
  author={Jeffrey D. Saffer and Cory Albright and Augustin J. Calapristi and Guang Chen and Vernon L. Crow and Scott D. Decker and Kevin M. Groch and Susan L. Havre and Jo{\"e}l M. Malard and Tonya J. Martin and Nancy E. Miller and Philip J. Monroe and Lucy T. Nowell and Deborah A. Payne and Jorge F. Reyes Spindola and Randall E. Scarberry and Heidi J. Sofia and Lisa C. Stillwell and Gregory S. Thomas and Sarah J. Thurston and Leigh Williams and S. Zabriskie and Mg Hicks},
  year={2001}
}
The volumes and diversity of information in the discovery, development, and business processes within the chemical and life sciences industries require new approaches for analysis. Traditional list- or spreadsheet-based methods are easily overwhelmed by large amounts of data. Furthermore, generating strong hypotheses and, just as importantly, ruling out weak ones, requires integration across different experimental and informational sources. We have developed a framework for this integration… 
Analytics for massive heat maps
TLDR
A novel method is presented that provides an interactive visual display for massive heat maps and shows how a massive heat map can be decomposed into multiple levels of abstraction to represent the underlying macrostructures.