In information visualization every method performs best in its own range of plotting density. When the available area for the visualization is unknown or when the data is supplied in packages of various sizes, the best suited method cannot be chosen in advance, and the wrong choice leads to the problems of under- or overplotting. This note suggests a solution to dynami-cally change the visualization method based on the sample size and plotting area. The concept is illustrated with an example application for multivariate data. Sug-gested future work includes applying the solution to other data types, defining the switching boundaries and fading functions. The proposed dynamic switching of methods increases the plotting scalability of interactive data visualizations and thus can improve the usability of information-intense graphical user interfaces.
|Title of host publication||NordiCHI '14: Proceedings of the 8th Nordic Conference on Human-Computer Interaction: Fun, Fast, Foundational|
|Number of pages||4|
|Publication status||Published - 2014|
|MoE publication type||A4 Article in a conference publication|
- Data graphics; information visualization; data visualiza-tion; view transformations; visual structures; big data; overplotting; underplotting; HCI; GUI; user interface; plotting scalability; plotting density