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.

Additional Metadata
Stakeholder MonetDB Solutions BV
Persistent URL dx.doi.org/10.14778/3007263.3007288
Project The SciLens-II Infrastructure, Big Data at work , Commit: Time Trails (P019)
Conference International Conference on Very Large Data Bases
Grant This work was funded by the The Netherlands Organisation for Scientific Research (NWO); grant id nwo/621.016.201 - The Scilens-II Infrastructure, Big Data at work
Citation
Sellam, T.H.J, Cijvat, C.P, Koopmanschap, R.A, & Kersten, M.L. (2016). Blaeu: Mapping and navigating large tables with cluster analysis. In Proceedings of the VLDB Endowment (pp. 1477–1480). doi:10.14778/3007263.3007288