Stress Maps: Analysing Local Phenomena in Dimensionality Reduction Based Visualisations

Seifert, Christin; Sabol, Vedran; Kienreich, Wolfgang

Stress Maps: Analysing Local Phenomena in Dimensionality Reduction Based Visualisations

Files

013-018.pdf (419.28 KB)

Date

2010

Authors

Seifert, Christin
Sabol, Vedran
Kienreich, Wolfgang

Publisher

The Eurographics Association

Abstract

Challenges in Visual Analytics frequently involve massive repositories, which do not only contain a large number of information artefacts, but also a high number of relevant dimensions per artefact. Dimensionality reduction algorithms are commonly used to transform high-dimensional data into low- dimensional representations which are suitable for visualisation purposes. For example, Information Landscapes visualise high-dimensional data in two dimensions using distance-preserving projection methods. The inaccuracies introduced by such methods are usually expressed through a global stress measure which does not provide insight into localised phenomena. In this paper, we propose the use of Stress Maps, a combination of heat maps and information landscapes, to support algorithm development and optimization based on local stress measures. We report on an application of Stress Maps to a scalable text projection algorithm and describe two categories of problems related to localised stress phenomena which we have identified using the proposed method.

        @inproceedings{:10.2312/PE/EuroVAST/EuroVAST10/013-018
,
booktitle = {EuroVAST 2010: International Symposium on Visual Analytics Science and Technology
},
editor = {Joern Kohlhammer and Daniel Keim
},
title = {{Stress Maps: Analysing Local Phenomena in Dimensionality Reduction Based Visualisations
}},
author = {Seifert, Christin and 
Sabol, Vedran and 
Kienreich, Wolfgang
},
year = {2010
},
publisher = {The Eurographics Association
},
ISBN = {978-3-905673-74-6
},
DOI = {/10.2312/PE/EuroVAST/EuroVAST10/013-018
}
}