UpSet: Visualization of Intersecting Sets by Alexander Lex, Nils Gehlenborg, Hendrik Strobelt, Romain Vuillemot, Hanspeter Pfister.
From the post:
Understanding relationships between sets is an important analysis task that has received widespread attention in the visualization community. The major challenge in this context is the combinatorial explosion of the number of set intersections if the number of sets exceeds a trivial threshold. To address this, we introduce UpSet, a novel visualization technique for the quantitative analysis of sets, their intersections, and aggregates of intersections.
UpSet is focused on creating task-driven aggregates, communicating the size and properties of aggregates and intersections, and a duality between the visualization of the elements in a dataset and their set membership. UpSet visualizes set intersections in a matrix layout and introduces aggregates based on groupings and queries. The matrix layout enables the effective representation of associated data, such as the number of elements in the aggregates and intersections, as well as additional summary statistics derived from subset or element attributes.
Sorting according to various measures enables a task-driven analysis of relevant intersections and aggregates. The elements represented in the sets and their associated attributes are visualized in a separate view. Queries based on containment in specific intersections, aggregates or driven by attribute filters are propagated between both views. UpSet also introduces several advanced visual encodings and interaction methods to overcome the problems of varying scales and to address scalability.
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Definitely paper and software to have on hand while you read and explore AggreSet, which I mentioned yesterday in: Exploring and Visualizing Pre-Topic Map Data.
Interested to hear your thoughts comparing the two.
Something to keep in mind is that topic map authoring can be thought of as a waterfall model, where ontological decisions, merging criteria, etc. are worked out in advance versus using an agile methodology, that explores data and iterates over it, allowing the topic map to grow and evolve.
An evolutionary topic map could well miss places the waterfall method would catch but if no one goes there, or not often, is that a real issue?
I must admit, I am less than fond of “agile” methodologies but that is from a bad experience where an inappropriate person was in charge of a project and thought a one paragraph description was sufficient for a new CMS system built upon subversion. Sufficient because the project was “agile.” Fortunately that project was tanked after a long struggle with management.
Perhaps I should think about the potential use of “agile” methodologies in authoring and evolving topic maps.
Suggestions/comments?