Abstract
Users can better understand complex data sets by combining insights from multiple coordinated visual displays that include relevant domain knowledge. When dealing with multidimensional data and clustering results, the most familiar displays and comprehensible are 1- and 2-dimensional projections (histograms, and scatterplots). Other easily understood displays of domain knowledge 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’ domain knowledge for understanding clustering results. Our examples present hierarchical clustering of gene expression data, coordinated with a parallel coordinates view and with the gene annotation and gene ontology.
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Seo, J., Shneiderman, B. (2005). A Knowledge Integration Framework for Information Visualization. In: Hemmje, M., Niederée, C., Risse, T. (eds) From Integrated Publication and Information Systems to Information and Knowledge Environments. Lecture Notes in Computer Science, vol 3379. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31842-2_21
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DOI: https://doi.org/10.1007/978-3-540-31842-2_21
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