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Towards Data-Driven Multilinear Metro Maps

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Diagrammatic Representation and Inference (Diagrams 2020)

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Abstract

Traditionally, most schematic metro maps as well as metro map layout algorithms adhere to an octolinear layout style with all paths composed of horizontal, vertical, and \(45^\circ \)-diagonal edges. Despite growing interest in more general multilinear metro maps, generic algorithms to draw metro maps based on a system of \(k \ge 2\) not necessarily equidistant slopes have not been investigated thoroughly. We present and implement an adaptation of the octolinear mixed-integer linear programming approach of Nöllenburg and Wolff (2011) that can draw metro maps schematized to any set \(\mathcal {C}\) of arbitrary orientations. We further present a data-driven approach to determine a suitable set \(\mathcal {C}\) by either detecting the best rotation of an equidistant orientation system or by clustering the input edge orientations using a k-means algorithm. We demonstrate the new possibilities of our method in a real-world case study.

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Notes

  1. 1.

    \(f_1\) emphasizes line straightness, \(f_2\) the topographicity and \(f_3\) compactness of an optimal layout.

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Acknowledgments

We thank Maxwell J. Roberts for discussions about non-standard linearity models.

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Authors and Affiliations

  1. Algorithms and Complexity Group, TU Wien, Vienna, Austria

    Soeren Nickel & Martin Nöllenburg

Authors
  1. Soeren Nickel
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  2. Martin Nöllenburg
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Corresponding author

Correspondence to Martin Nöllenburg .

Editor information

Editors and Affiliations

  1. Tallinn University of Technology, Tallinn, Estonia

    Ahti-Veikko Pietarinen

  2. Edinburgh Napier University, Edinburgh, UK

    Peter Chapman

  3. University of Groningen, Groningen, The Netherlands

    Leonie Bosveld-de Smet

  4. Université de Lorraine, Nancy, France

    Valeria Giardino

  5. Columbia University, New York, NY, USA

    James Corter

  6. University of Liverpool, Liverpool, UK

    Sven Linker

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Nickel, S., Nöllenburg, M. (2020). Towards Data-Driven Multilinear Metro Maps. In: Pietarinen, AV., Chapman, P., Bosveld-de Smet, L., Giardino, V., Corter, J., Linker, S. (eds) Diagrammatic Representation and Inference. Diagrams 2020. Lecture Notes in Computer Science(), vol 12169. Springer, Cham. https://doi.org/10.1007/978-3-030-54249-8_12

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  • DOI: https://doi.org/10.1007/978-3-030-54249-8_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-54248-1

  • Online ISBN: 978-3-030-54249-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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