Visualization Process. Alark Joshi

Transcription

1 Visualization Process Alark Joshi

2 Task-specific Visualization Design LA Treinish, Task-specific visualization design, IEEE Computer Graphics and Applications, 1999 Generalized visualization systems are less suitable for environments with specific tasks and user needs Prototypes help with defining/refining user needs Iterative process of developing novel techniques to converge on meeting user needs

3 Class I 2D visualization Provide colormapped or contoured 2D scalar fields Minimal interaction at a specific layer Can only show a few parameters simultaneously

4 Class II - 2D and 2.5D analysis - Precipitable water as the height - Pseudo-colored by temperature - Arrows indicate wind direction and speed is encoded in terms of color - Local coastline (black) - State boundaries (white) - River map (blue) Precipitable water as a surface

5 Class III 3D browsing - Cartographically projected true height of the terrain - Coastline (black) - State boundaries (white) - Blue puddles show regions of heavy rainfall - Vector arrows show surface wind velocity color-coded with speed - Visualization used to predict rainfall for the closing ceremony of the Atlanta Olympics in 1996

6 Class III 3D browsing - Cartographically projected true height of the terrain - Coastline (black) - State boundaries (white) - Blue puddles show regions of heavy rainfall - Vector arrows show surface wind velocity color-coded with speed - Visualization used to predict rainfall for the closing ceremony of the Atlanta Olympics in 1996

7 Class IV 3D analysis - Pseudo-colored Precipitation (Surface variable) - Relative humidity (Upper air variable) shown as a translucent white surface - Temperature shown as a vertical slice - Coastline (black) - State boundaries (white) - Vector arrows encode speed and direction of wind velocity

8 Sequence illustrating typical use

9 Blog comments Eddie The application of design principles based on user needs to visualization certainly stands to reason provides a concrete example Danny This paper argues that one size of software does not fit all. Tim proposed design process can and should be applied to the development of all visualization tools, whether the user audience is very large or very small.

10 Overview of the Process

11 Demo Voreen Colorbrewer Map of the Market

12 Visualization Pipeline Simulation Database Raw Data Filtered Data Mapping Visualize Acquisition (scanners, sensors, ) Filtering Rendering

13 Filtering Data input -> Data output Data format conversion Clipping/cropping/denoising Slicing Resampling Interpolation/approximation Classification/segmentation

14 Mapping Data input -> Graphical Primitives Scalar field -> Surface, Lines Vector field -> Vectors/Arrows/Streamlines Tensor field -> Tensor glyphs/ellipsoids 3D Field -> volume visualization High dimensional data -> Map to 2D/3D Image credits: SCI Utah, Daniel Weiskopf

15 Rendering Render graphics primitives such as Points Lines Surfaces Volumes With attributes such as Color Texture Transparency

16 Image credits: Voreen Visualization Pipeline

17 Visualization Pipeline Example: simulation of flow within a fluid around a wing

18 Image credits: van Wijk, Value of Visualization Cyclical Model

19 Cyclical Model prefuse.org - set of software tools for creating rich interactive data visualizations. - original prefuse toolkit provides a visualization framework for Java - prefuse flare toolkit provides visualization and animation tools for ActionScript and the Adobe Flash Player. Image credits: Jeff Heer, prefuse

20 Cyclical Model

21 Video/Movie mode Scenarios

22 Feature Tracking Scenarios

23 Scenarios Interactive post processing/visualization

24 Scenarios Interactive computational steering

25 Value of Visualization Jarke J. van Wijk, "The Value of Visualization," IEEE Visualization, How to assess the value of visualization? We all agree that a visualization should be effective and efficient Van Wijk provides an economic model of visualization where he discusses the value in terms of associated costs and gains

26 Economic Model of Visualization D Data V Visualization S - Specification P Perception/Cognition of the user (mental model) K Knowledge E Exploration through interaction Image credits: van Wijk, Value of Visualization

27 Discussion Technology Innovation Art Does it merely serve as art? Should we be learning from the field of art? Science Is there a Science of Visualization?

28 Blog comments Josh Negative Knowledge occurs when a visualization misleads a user to gaining false or "negative" knowledge Bill If Visualization is considered Tech should the bulk of the funding be going to applications that have the promise of becoming mainstream technology? Shouldn t we be starting more companies?

29 Blog comments Peter does not present a consistent set of ideas that lead to a conclusion or conclusions. raises many interesting questions regarding the value of visualization. personally have a hard time believing that it can be effectively assessed. Archana Too much interaction will make the visualization more subjective and customization can be misleading. Danny liked the comment in the paper the purpose of vis is funding, not insight