Just a short post, but another demo is online.

It is a demon­stra­tion of the “elas­tic list” prin­ci­ple for brows­ing multi-facetted data struc­tures. Click any num­ber of list entries to query the data­base for a com­bi­na­tion of the selected attrib­utes. If you cre­ate an “impos­si­ble” con­fig­u­ra­tion, your selec­tion will be reduced until a match is possible.

The exam­ple data is based on the Noble prize win­ners dataset used in the Fla­menco facet browser.

Elas­tic lists enhance tra­di­tional facet brows­ing approaches by • visu­al­iz­ing rel­a­tive pro­por­tions (weights) of meta­data val­ues by size • visu­al­iz­ing unusu­al­ness of a meta­data weight by bright­ness • and ani­mated fil­ter­ing transitions.

In unfil­tered view, the bright­ness shows a trend mea­sure, indi­cat­ing a ris­ing num­ber of prices of the last years.

In fil­tered views, a brighter back­ground indi­cates a higher weight of the meta­data value com­pared to the over­all distribution.

If, for instance, you click “peace” as in the exam­ple above, you will see that “female” and “Switzer­land” are much brighter, indi­cat­ing that the pro­por­tion of women and Swiss is much higher in this con­text than com­pared to the whole data set. That’s inter­est­ing infor­ma­tion and could also be used to char­ac­ter­ize the result set of a key­word query or any other col­lec­tion in terms of its “char­ac­ter­is­tic” meta­data val­ues. Besides that, it fos­ters under­stand­ing of how meta­data val­ues are cor­re­lated with each other, which is often inter­est­ing infor­ma­tion itself.

You can also switch on lit­tle sparklines to see the tem­po­ral dis­tri­b­u­tion of each meta­data value:

As promised, here is an update to the tag maps appli­ca­tion I intro­duced below along with some explanations.

For the impa­tient: HERE’S THE LINK

(Update again: The lat­est ver­sion can be found here)

And for the curi­ous: Here’s the expla­na­tions: (more…)