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Network Visualization

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Abstract

Data visualization is the art and science of mapping data to graphical variables. In this context, networks give rise to unique difficulties because of inherent dependencies among their elements. We provide a high-level overview of the main challenges and common techniques to address them. They are illustrated with examples from two application domains, social networks and automotive engineering. The chapter concludes with opportunities for future work in network visualization.

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Notes

  1. 1.

    In automotive terminology, these are the bus systems that components are connected to, such as the CAN, MOST, or FlexRay bus. These domain-specific details are not relevant for the discussion here, and we hence simply refer to them as “subsystems.”

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Authors and Affiliations

  1. Department of Humanities, Social and Political Sciences, ETH Zurich, Zurich, Switzerland

    Ulrik Brandes

  2. Department of Computer Science, University of Stuttgart, Stuttgart, Germany

    Michael Sedlmair

Authors
  1. Ulrik Brandes
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  2. Michael Sedlmair
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Correspondence to Ulrik Brandes .

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Editors and Affiliations

  1. Department of Mathematics, LMU Munich, Munich, Germany

    Francesca Biagini

  2. Department of Statistics, LMU Munich, Munich, Germany

    Göran Kauermann

  3. Department of Mathematics, LMU Munich, Munich, Germany

    Thilo Meyer-Brandis

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Brandes, U., Sedlmair, M. (2019). Network Visualization. In: Biagini, F., Kauermann, G., Meyer-Brandis, T. (eds) Network Science. Springer, Cham. https://doi.org/10.1007/978-3-030-26814-5_2

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