Interactive Model Prototyping in Visualization Space

O. Daæ Lampe
Christian Michelsen Research, Norway & Department of Informatics, University of Bergen, Norway

H. Hauser
Department of Informatics, University of Bergen, Norway

Ladda ner artikel

Ingår i: Proceedings of SIGRAD 2011. Evaluations of Graphics and Visualization — Efficiency; Usefulness; Accessibility; Usability; November 17-18; 2011; KTH; Stockholm; Sweden

Linköping Electronic Conference Proceedings 65:7, s. 43-51

Visa mer +

Publicerad: 2011-11-21

ISBN: 978-91-7393-008-6

ISSN: 1650-3686 (tryckt), 1650-3740 (online)


Researching formal models that explain selected natural phenomena of interest is a central aspect of most scientific work. A tested and confirmed model can be the key to classification; knowledge crystallization; and prediction.With this paper we propose a new approach to rapidly draft; fit and quantify model prototypes in visualization space. We also show that these models can provide important insights and accurate metrics about the original data. Using our technique; which is similar to the statistical concept of de-trending; data that behaves according to the model is de-emphasized; leaving only outliers and potential model flaws for further inspection. Moreover; we provide several techniques to assist the user in the process of prototyping such models. We demonstrate the usability of this approach in the context of the analysis of streaming process data from the Norwegian oil and gas industry; and on weather data; investigating the distribution of temperatures over the course of a year.


Inga nyckelord är tillgängliga


[CD86] CHIN R.; DYER C.: Model-based recognition in robot vision. ACM Comp. Surveys (CSUR) 18; 1 (1986); 67–108. 2

[DH11a] DAAE LAMPE O.; HAUSER H.: Curve density estimates. Comp. Graphics Forum 30; 3 (2011); 633–642. 7

[DH11b] DAAE LAMPE O.; HAUSER H.: Interactive visualization of streaming data with kernel density estimation. In Proceedings of the IEEE Pacific Visualization Symposium (PacificVis 2011) (March 2011); pp. 171–178. 2; 4

[DKH10] DAAE LAMPE O.; KEHRER J.; HAUSER H.: Visual analysis of multivariate movement data using interactive difference views. In Proceedings of Vision; Modeling; and Visualization (VMV 2010) (2010); pp. 315–322. 2; 4

[dR99] DESJARDINS M.; RHEINGANS P.: Visualization of high-dimensional model characteristics. In Workshop on New Paradigms in Information Visualization and Manipulation (1999); pp. 6–8. 2

[GS99] GESÙ V. D.; STAROVOITOV V. V.: Distance-based functions for image comparison. Pattern Recognition Letters 20; 2 (1999); 207–214. 4

[LKG98] LÖFFELMANN H.; KUC? ERA T.; GRÖLLER E.: Visualizing Poincaré maps together with the underlying flow. In Mathematical Visualization - Algorithms; Applications and numerics. Springer; 1998; pp. 315–328. 2

[LS10] LIU Z.; STASKO J.: Mental Models; Visual Reasoning and Interaction in Information Visualization: A Top-down Perspective. IEEE Trans. Visualization and Computer Graphics 16; 6 (2010); 999–1008. 2

[Nor] NORWEGIAN METEOROLOGICAL INSTITUTE: eKlima. eklima.met.no. [Online; accessed Nov-2010]. 7

[NW99] NOCEDAL J.; WRIGHT S.: Numerical Optimization. Springer; 1999. 5

[PVH*03] POST F. H.; VROLIJK B.; HAUSER H.; LARAMEE R. S.; DOLEISCH H.: The State of the Art in Flow Visualization: Feature Extraction and Tracking. Computer Graphics Forum 22 (2003); 775–792. 2

[Rd00] RHEINGANS P.; DESJARDINS M.: Visualizing highdimensional predicitive model quality. In IEEE Visualization (2000); pp. 493–496. 2

[Sil01] SILVERT W.: Modelling as a discipline. International Journal of General Systems 30; 3 (2001); 261–282. 1

[SvW08] SHRINIVASAN Y. B.; VAN WIJK J. J.: Supporting the analytical reasoning process in information visualization. In CHI ’08: Proc. of SIGCHI on Human factors in computing systems (2008); pp. 1237–1246. 2

[Wal04] WALNUT D. F.: An Introduction to Wavelet Analysis. Springer; 2004. 2

[YXRW07] YANG D.; XIE Z.; RUNDENSTEINER E. A.; WARD M. O.: Managing discoveries in the visual analytics proc. SIGKDD Explor. Newsl. 9; 2 (2007). 2

[ZSBH08] ZAMBAL S.; SCHÖLLHUBER A.; BÜHLER K.; HLADUVKA J.: Fast and robust localization of the heart in cardiac MRI series. Proc. of Int. Conf. on Computer Vision Theory and Applications (2008). 2

Citeringar i Crossref