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Improvement of Disability Rights via Geographic Information Science

Author

Listed:
  • Sultan Kocaman

    (Department of Geomatics Engineering, Hacettepe University, 06800 Ankara, Turkey)

  • Nadire Ozdemir

    (Department of Philosophy and Sociology of Law, Faculty of Law, Ankara University, 06590 Ankara, Turkey)

Abstract

Rights, legal regulations, and practices often arise from societal and scientific developments, and societal transformations may originate from new legal regulations as well. Basic rights can be re-defined with advancements in science and technology. In such an evolutional loop, where mutual supply is obvious, combined legal and technological frameworks should be exercised and developed for practicing human rights. The main aim of this article is to propose a conceptual and methodological framework for the improvement of disability rights in the light of recent advancements in geographic information science (GIScience), in particular for those with motor disabilities, for whom questions related to “where” are essential. The concept of disability is discussed, considering different aspects, and a new methodological framework is proposed in which Geographic Information Systems (GIS), volunteered geographic information (VGI) and citizen science are at the core. In order to implement the framework at the national and international levels, a spatial data model should be developed first. The new data collection and interpretation approaches based on VGI, citizen science, and machine learning methods may help to realize equal rights for people with motor disabilities, by enabling improved access to education, health, and travel.

Suggested Citation

  • Sultan Kocaman & Nadire Ozdemir, 2020. "Improvement of Disability Rights via Geographic Information Science," Sustainability, MDPI, vol. 12(14), pages 1-17, July.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:14:p:5807-:d:386751
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    References listed on IDEAS

    as
    1. Strain, Lisa & Rajabifard, Abbas & Williamson, Ian, 2006. "Marine administration and spatial data infrastructure," Marine Policy, Elsevier, vol. 30(4), pages 431-441, July.
    2. Tao, Sui & He, Sylvia Y. & Kwan, Mei-Po & Luo, Shuli, 2020. "Does low income translate into lower mobility? An investigation of activity space in Hong Kong between 2002 and 2011," Journal of Transport Geography, Elsevier, vol. 82(C).
    3. Mei-Po Kwan, 2018. "The Limits of the Neighborhood Effect: Contextual Uncertainties in Geographic, Environmental Health, and Social Science Research," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 108(6), pages 1482-1490, November.
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    Cited by:

    1. Yildiz, Umit & Gürel, Murat & Kocaman, Sultan, 2022. "State liability and uncertainty perception on cadastral parcel area registry in Turkey," Land Use Policy, Elsevier, vol. 116(C).

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