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Designing a Semi-automatic Map Construction Process for the Effective Visualisation of Business Geodata

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Computational Science and Its Applications – ICCSA 2020 (ICCSA 2020)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12252))

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Abstract

This paper proposes a map construction process for the semi-automatic construction of thematic maps from business information data. Addressing a non-specialist user audience, the map construction process will allow a correct, at the same time effective cartographic visualisation for further (geo)visual analysis. Utilising the frequently disregarded geospatial component of existing business mass data, quality map representations facilitate the visual exploration, detection, and analysis of relevant spatial data distributions and structures hitherto unseen in the data. Presently, neither operational procedures nor appropriate software systems, such as BIS, DDS or GIS, are available in the industry for an effective map representation of the geocoded data. To put economic and business experts into a position to make full use of the geo coordinates present in the data, an easy-to-handle map construction process is required to exploit the full semantic and spatial potential of business data. Exemplified for an area diagram map, the map construction process discussed here provides the relevant tools and methods for the targeted audience.

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Author information

Authors and Affiliations

  1. Institute of Geosciences, University of Potsdam, Potsdam, Germany

    Marion Simon

  2. Computer Graphics System Group, Hasso Plattner Institute, University of Potsdam, Potsdam, Germany

    Hartmut Asche

Authors
  1. Marion Simon
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  2. Hartmut Asche
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Corresponding authors

Correspondence to Marion Simon or Hartmut Asche .

Editor information

Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Potenza, Italy

    Beniamino Murgante

  3. Chair- Center of ICT/ICE, Covenant University, Ota, Nigeria

    Sanjay Misra

  4. University of Cagliari, Cagliari, Italy

    Chiara Garau

  5. University of Cagliari, Cagliari, Italy

    Ivan Blečić

  6. Clayton School of Information Technology, Monash University, Clayton, VIC, Australia

    David Taniar

  7. Department of Information Science, Kyushu Sangyo University, Fukuoka, Japan

    Bernady O. Apduhan

  8. University of Minho, Braga, Portugal

    Ana Maria A. C. Rocha

  9. Polytechnic University of Bari, Bari, Italy

    Eufemia Tarantino

  10. Polytechnic University of Bari, Bari, Italy

    Carmelo Maria Torre

  11. Department of Neurology, University of Massachusetts Medical School, Worcester, MA, USA

    Yeliz Karaca

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Simon, M., Asche, H. (2020). Designing a Semi-automatic Map Construction Process for the Effective Visualisation of Business Geodata. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2020. ICCSA 2020. Lecture Notes in Computer Science(), vol 12252. Springer, Cham. https://doi.org/10.1007/978-3-030-58811-3_32

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  • DOI: https://doi.org/10.1007/978-3-030-58811-3_32

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-58810-6

  • Online ISBN: 978-3-030-58811-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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