Designing the Ontology of a Smart City Application for Measuring Multidimensional Urban Poverty

Abstract

This study tries to analyze and discuss the design process of a smart city application ontology for measuring multidimensional poverty at an urban scale. Starting from the links between smart city concept and human-centered development and moving on to the definition of multidimensional poverty, the literature indicates that there is a need for an orchestrated design of smart city applications for alleviating poverty in its wider sense, based on strong theoretical foundations. The study indicates that a volunteered geographic information (VGI) concept, alongside with a 3-level data structure, should be treated as integral parts of the proposed application structure that uses the human-centered theoretical approach as a baseline to alleviate poverty. The 3-level data structure encompasses a wide range of indicators, referring not only to demographic and spatiotemporal variables, but also covers all essential information for measuring multidimensional poverty index (MPI). Finally, the collected data from this application could be further exploited by local governments and policy makers, as valuable inputs for strategic planning of place-based policies. This study serves as an example of how a smart city application could be used as a tool to effectively improve human-centered policy implications on an urban scale.

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Acknowledgements

We would like to thank the editor and the two anonymous referees for their insightful comments.

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Correspondence to Anastasia Panori.

Appendix

Appendix

In the following section, all indicators for MPI components are presented based on Weziak-Bialowolska (2016) conceptualization of regional MPI for the EU countries.

  • Dimension 1: Health (2 out of 3)

    • Component 1.1: General health

      • PH010—Reporting bad or very bad conditions

    • Component 1.2: Unmet medical need due to lack of affordability and accessibility

      • PH040, PH050—Unmet need for medical examination or treatment because it was not affordable, there was a waiting list, or it was too far to travel/no means of transportation

    • Component 1.3: Unmet dental need due to lack of affordability and accessibility

      • PH060, PH070—Unmet need for dental examination or treatment because it was not affordable, there was a waiting list, or it was too far to travel/no means of transportation

  • Dimension 2: Education

    • Component 2.1: Educational attainment

      • PB010, PB140, PE010, PE040—A person of more than 24 years not having at least upper secondary education or in the age range 16–24 years who has finished no more than lower secondary education and is not involved in further education (based on early school leaver definition)

  • Dimension 3: Living standards (1 out of 3)

    • Component 3.1: Material deprivation (3 out of 9)

      • HS070, HS090, HS100, HS110—Household cannot afford a telephone (including a mobile phone), a computer, a washing machine, and a car.

      • HS010, HS011, HS020, HS021—Households with arrears on mortgage or rent payments or utility bills

      • HS040—Lack of capacity in a household to afford paying for 1-week annual holiday away from home

      • HS050—Lack of capacity in a household to afford a meal with meat, chicken, and fish (or vegetarian equivalent) every second day

      • HS060—Lack of capacity to face unexpected financial expenses

      • HH050—Household without ability to keep home adequately warm

    • Component 3.2: Housing problems (2 out of 4)

      • HH030—Crowding index (average number of people per room available to the household) > 2

      • HH040, HH080/HH081, HS160—Problems with dwelling such as the following: leaking roof, damp walls/floors/foundation, or rotten window frames or floor; too dark, not enough light; without bath or shower for sole use in dwelling

    • Component 3.3: Environment (2 out of 3)

      • HS170, HS180, HS190—Household experiences such as the following: noise from neighbors or from the street; pollution, grime, or other environmental problems; crime, violence, or vandalism in the area

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Panori, A., Kakderi, C. & Tsarchopoulos, P. Designing the Ontology of a Smart City Application for Measuring Multidimensional Urban Poverty. J Knowl Econ 10, 921–940 (2019). https://doi.org/10.1007/s13132-017-0504-y

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Keywords

  • Smart cities
  • Multidimensional poverty
  • Development
  • Policy design