Original Article

Information Visualization (2006) 5, 62–76. doi:10.1057/palgrave.ivs.9500116

Matrices or node-link diagrams: which visual representation is better for visualising connectivity models?

René Keller1, Claudia M Eckert1 and P John Clarkson1

1Engineering Design Centre, Department of Engineering, University of Cambridge, Trumpington Street, Cambridge, CB2 1PZ, UK

Correspondence: René Keller, Engineering Design Centre, Department of Engineering, University of Cambridge, Trumpington Street, Cambridge, CB2 1PZ, U.K. Tel.: +44 1223 332828; Fax: +44 1223 766956; E-mail: rk313@cam.ac.uk

Received 31 August 2005; Revised 8 December 2005; Accepted 0  2006; Published online 7 April 2006.

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Abstract

Adjacency matrices or DSMs (design structure matrices) and node-link diagrams are both visual representations of graphs, which are a common form of data in many disciplines. DSMs are used throughout the engineering community for various applications, such as process modelling or change prediction. However, outside this community, DSMs (and other matrix-based representations of graphs) are rarely applied and node-link diagrams are very popular. This paper will examine, which representation is more suitable for visualising graphs. For this purpose, several user experiments were conducted that aimed to answer this research question in the context of product models used, for example in engineering, but the results can be generalised to other applications. These experiments identify key factors on the readability of graph visualisations and confirm work on comparisons of different representations. This study widens the scope of readability comparisons between node-link and matrix-based representations by introducing new user tasks and replacing simulated, undirected graphs with directed ones employing real-world semantics.

Keywords:

Graph visualisation, readability, evaluation, design structure matrix, engineering change

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Interactive Visualization and Data Analysis, Masters program at Danube University Krems, Austria