A Knowledge Integration Framework for Information Visualization (2004)

Abstract

Users can better understand complex data sets by combining insights from multiple coordinated visual displays that include relevant domain knowl-edge. When dealing with multidimensional data and clustering results, the most familiar displays and comprehensible are 1- and 2-dimensional projections (his-tograms, and scatterplots). Other easily understood displays of domain knowl-edge are tabular and hierarchical information for the same or related data sets. The novel parallel coordinates view [6] powered by a direct-manipulation search, offers strong advantages, but requires some training for most users. We provide a review of related work in the area of information visualization, and introduce new tools and interaction examples on how to incorporate usersdo-main knowledge for understanding clustering results. Our examples present hi-erarchical clustering of gene expression data, coordinated with a parallel coor-dinates view and with the gene annotation and gene ontology.