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Depth Cues and Density in Temporal Parallel Coordinates
Linköping University, Department of Science and Technology, Visual Information Technology and Applications (VITA). Linköping University, The Institute of Technology.
Linköping University, Department of Science and Technology, Visual Information Technology and Applications (VITA). Linköping University, The Institute of Technology.ORCID iD: 0000-0002-9288-5322
Linköping University, Department of Science and Technology, Visual Information Technology and Applications (VITA). Linköping University, The Institute of Technology.
2007 (English)In: Proceedings of Eurographics/IEEE VGTC Symposium on Visualization, Norrköping, Sweden, Aire-la-Ville, Switzerland: Eurographics Association , 2007, 35-42 p.Conference paper, Published paper (Other academic)
Abstract [en]

This paper introduces Temporal Density Parallel Coordinates (TDPC) and Depth Cue Parallel Coordinates (DCPC) which extend the standard 2D parallel coordinates technique to capture time-varying dynamics. The proposed techniques can be used to analyse temporal positions of data items as well as temporal positions of changes occurring using 2D displays. To represent temporal changes, polygons (instead of traditional lines) are rendered in parallel coordinates. The results presented show that rendering polygons is superior at revealing large temporal changes. Both TDPC and DCPC have been efficiently implemented on the GPU allowing the visualization of thousands of data items over thousands of time steps at interactive frame rates.

Place, publisher, year, edition, pages
Aire-la-Ville, Switzerland: Eurographics Association , 2007. 35-42 p.
National Category
Computer Science
Identifiers
URN: urn:nbn:se:liu:diva-13216DOI: 10.2312/VisSym/EuroVis07/035-042OAI: oai:DiVA.org:liu-13216DiVA: diva2:18058
Available from: 2008-05-07 Created: 2008-05-07 Last updated: 2015-05-27
In thesis
1. Efficient Information Visualization of Multivariate and Time-Varying Data
Open this publication in new window or tab >>Efficient Information Visualization of Multivariate and Time-Varying Data
2008 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Data can be found everywhere, for example in the form of price, size, weight and colour of all products sold by a company, or as time series of daily observations of temperature, precipitation, wind and visibility from thousands of stations. Due to their size and complexity it is intrinsically hard to form a global overview and understanding of them. Information visualization aims at overcoming these difficulties by transforming data into representations that can be more easily interpreted.

This thesis presents work on the development of methods to enable efficient information visualization of multivariate and time-varying data sets by conveying information in a clear and interpretable way, and in a reasonable time. The work presented is primarily based on a popular multivariate visualization technique called parallel coordinates but many of the methods can be generalized to apply to other information visualization techniques.

A three-dimensional, multi-relational version of parallel coordinates is presented that enables a simultaneous analysis of all pairwise relationships between a single focus variable and all other variables included in the display. This approach permits a more rapid analysis of highly multivariate data sets. Through a number of user studies the multi-relational parallel coordinates technique has been evaluated against standard, two-dimensional parallel coordinates and been found to better support a number of different types of task.

High precision density maps and transfer functions are presented as a means to reveal structure in large data displayed in parallel coordinates. These two approaches make it possible to interactively analyse arbitrary regions in a parallel coordinates display without risking the loss of significant structure.

Another focus of this thesis relates to the visualization of time-varying, multivariate data. This has been studied both in the specific application area of system identification using volumetric representations, as well as in the general case by the introduction of temporal parallel coordinates.

The methods described in this thesis have all been implemented using modern computer graphics hardware which enables the display and manipulation of very large data sets in real time. A wide range of data sets, both synthetically generated and taken from real applications, have been used to test these methods. It is expected that, as long as the data have multivariate properties, they could be employed efficiently.

Place, publisher, year, edition, pages
Institutionen för teknik och naturvetenskap, 2008
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1191
Keyword
Information visualization, parallel coordinates, interactive analysis, multivariate data, time-varying data, GPU, hardware graphics
National Category
Computer Science
Identifiers
urn:nbn:se:liu:diva-11643 (URN)978-91-7393-878-5 (ISBN)
Public defence
2008-05-30, K3, Kåkenhus, Campus Norrköping, Linköpings universitet, Norrköping, 09:15 (English)
Opponent
Supervisors
Available from: 2008-05-07 Created: 2008-05-07 Last updated: 2010-12-06

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Johansson, JimmyLjung, PatricCooper, Matthew

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