The Thrill of Discovery: Information Visualisation for High-​Dimensional Spaces’

I atten­ded today the Prof. Ben Shnei­der­man lec­ture ‘The Thrill of Dis­cov­ery: Inform­a­tion Visu­al­isa­tion for High-​Dimensional Spaces’ at the Centre for HCI Design, City Uni­ver­sity of London.

Abstract (from http://​www​.soi​.city​.ac​.uk/​n​e​w​s​/​r​e​s​e​a​r​c​h​s​e​m​i​n​a​r​s​.​h​tml)

Inter­act­ive inform­a­tion visu­al­isa­tion provide research­ers with remark­able tools for dis­cov­ery. By com­bin­ing power­ful data min­ing meth­ods with user-​controlled inter­faces, users are begin­ning to bene­fit from these potent tele­scopes for high-​dimensional spaces. They can begin with an over­view, zoom in on areas of interest, fil­ter out unwanted items, and then click for details-on-demand. With care­ful design and effi­cient algorithms, the dynamic quer­ies approach to data explor­a­tion can provide 100msec updates even for million-​record databases.

This talk will start by review­ing the grow­ing com­mer­cial suc­cess stor­ies such as www​.spot​fire​.com, www​.smart​money​.com/​m​a​r​k​e​t​map and www​.hive​group​.com. Then it will cover recent research pro­gress for visual explor­a­tion of large time series data applied to fin­an­cial, Ebay auc­tion, and gen­omic data (www​.cs​.umd​.edu/​h​c​i​l​/​t​i​m​e​s​e​a​r​c​her ).

Our next step was to com­bine these key ideas to pro­duce the Hier­arch­ical Clus­ter­ing Explorer 3.0 that now includes the rank-​by-​feature frame­work (www​.cs​.umd​.edu/​h​c​i​l​/​hce). By judi­ciously choos­ing from appro­pri­ate rank­ing cri­teria for low-​dimensional axis-​parallel pro­jec­tions, users can loc­ate desired fea­tures of higher dimen­sional spaces. Demon­stra­tions will be shown.”

The talk was great, it covered more than what was prom­ised in the above abstract. One not­able men­tion would be ManyEyes which brings a col­lab­or­at­ive aspect within inform­a­tion visualisation.