The emerging field of Progressive Visual Analytics (PVA in what follows) deals with the objective of progressively create the final visualization through a series of intermediate visual results, affected by a degree of uncertainty and, in some cases, a non monotonic behaviour. According to that, it is a critical issue providing the user with no confusing visualization and that results in a novel point of view on stability and consistency. This position paper deals with the novel and challenging issues that PVA poses in term of visual stability and consistency, providing a preliminary framework in which this problem can be contextualized, measured, and formalized. In particular, the framework proposes a set of metrics, able to explore both data and visual changes; a preliminary case study demonstrates their applicability and advantages in adequately representing data changes in a visualization.
On visual stability and visual consistency for Progressive Visual Analytics / Angelini, Marco; Santucci, Giuseppe. - 3:(2017), pp. 335-341. (Intervento presentato al convegno 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2017 tenutosi a Porto; Portugal) [10.5220/0006269703350341].
On visual stability and visual consistency for Progressive Visual Analytics
Angelini, Marco
;Santucci, Giuseppe
2017
Abstract
The emerging field of Progressive Visual Analytics (PVA in what follows) deals with the objective of progressively create the final visualization through a series of intermediate visual results, affected by a degree of uncertainty and, in some cases, a non monotonic behaviour. According to that, it is a critical issue providing the user with no confusing visualization and that results in a novel point of view on stability and consistency. This position paper deals with the novel and challenging issues that PVA poses in term of visual stability and consistency, providing a preliminary framework in which this problem can be contextualized, measured, and formalized. In particular, the framework proposes a set of metrics, able to explore both data and visual changes; a preliminary case study demonstrates their applicability and advantages in adequately representing data changes in a visualization.File | Dimensione | Formato | |
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