In this paper we integrate radviz and parallel coordinates, two methods able to handle multidimensional datasets, exploiting their contrasting characteristics. From on side radviz offers good direct data manipulation (i.e., brushing) techniques and low cluttering but it fails in providing visualization of quantitative information; conversely, parallel coordinates clearly shows the values of data attributes and their ranges but suffers from high cluttering also on small datasets and presents tedious manipulation techniques. We developed a prototype, called SpringView, that allows for simultaneously viewing both radviz and parallel coordinates and implements several useful techniques to manipulate the data, both interactively and, more interestingly, automatically. We challenged our approach against two well know multidimensional datasets, proving its effectiveness.
Springview: Cooperation of radviz and parallel coordinates for view optimization and clutter reduction / E., Bertini; L., Dell'Aquila; Santucci, Giuseppe. - STAMPA. - 2005:(2005), pp. 22-29. (Intervento presentato al convegno 3rd International Conference on Coordinated and Multiple Views in Exploratory Visualization tenutosi a London, ENGLAND nel JUL 05, 2005) [10.1109/cmv.2005.17].
Springview: Cooperation of radviz and parallel coordinates for view optimization and clutter reduction
SANTUCCI, Giuseppe
2005
Abstract
In this paper we integrate radviz and parallel coordinates, two methods able to handle multidimensional datasets, exploiting their contrasting characteristics. From on side radviz offers good direct data manipulation (i.e., brushing) techniques and low cluttering but it fails in providing visualization of quantitative information; conversely, parallel coordinates clearly shows the values of data attributes and their ranges but suffers from high cluttering also on small datasets and presents tedious manipulation techniques. We developed a prototype, called SpringView, that allows for simultaneously viewing both radviz and parallel coordinates and implements several useful techniques to manipulate the data, both interactively and, more interestingly, automatically. We challenged our approach against two well know multidimensional datasets, proving its effectiveness.File | Dimensione | Formato | |
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