Blaeu: Mapping and Navigating Large Tables with Cluster Analysis

Blaeu is an interactive database exploration tool. Its aim is to guide casual users through large data tables, ultimately triggering insights and serendipity. To do so, it relies on a double cluster analysis mechanism. It clusters the data vertically: it detects themes, groups of mutually dependent columns that highlight one aspect of the data. Then it clusters the data horizontally. For each theme, it produces a data map, an interactive visualization of the clusters in the table. The data maps summarize the data. They provide a visual synopsis of the clusters, as well as facilities to inspect their content and annotate them. But they also let the users navigate further. Our explorers can change the active set of columns or drill down into the clusters to refine their selection. Our prototype is fully operational, ready to deliver insights from complex databases.

[1]  Wei-Yin Loh,et al.  Classification and regression trees , 2011, WIREs Data Mining Knowl. Discov..

[2]  Abraham Silberschatz,et al.  DataPlay: interactive tweaking and example-driven correction of graphical database queries , 2012, UIST.

[3]  Ali S. Hadi,et al.  Finding Groups in Data: An Introduction to Chster Analysis , 1991 .

[4]  Pat Hanrahan,et al.  Polaris: a system for query, analysis and visualization of multi-dimensional relational databases , 2000, IEEE Symposium on Information Visualization 2000. INFOVIS 2000. Proceedings.

[5]  Leo Breiman,et al.  Classification and Regression Trees , 1984 .

[6]  Martin L. Kersten,et al.  Cluster-Driven Navigation of the Query Space , 2016, IEEE Transactions on Knowledge and Data Engineering.