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

  • Anastasia Panori
  • Christina Kakderi
  • Panagiotis Tsarchopoulos
Article

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.

Keywords

Smart cities Multidimensional poverty Development Policy design 

Notes

Acknowledgements

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

References

  1. Adera, E. O., Waema, T. M., & May, J. (2014). ICT pathways to poverty reduction: empirical evidence from East and Southern Africa. IDRC.Google Scholar
  2. Adeya, C. N. (2002). ICTs and poverty: a literature review. Ottawa, IDRC.Google Scholar
  3. Alkire, S., Apablaza, M., & Jung, E. (2014). Multidimensional poverty measurement for EU-SILC countries. OPHI Research in Progress, 3, 66.Google Scholar
  4. Alkire, S., Foster, J. E., Seth, S., Santos, M. E., Roche, J. M., and Ballon, P. (2015). Multidimensional poverty measurement and analysis. Oxford: Oxford University Press, ch. 9.Google Scholar
  5. Antonelli, C. (2000). Collective knowledge communication and innovation: the evidence of technological districts. Regional Studies, 34(6), 535–547.CrossRefGoogle Scholar
  6. Apablaza, M., & Yalonetzky, G. (2013). Decomposing multidimensional poverty dynamics. Young Lives Working Paper, Forthcoming.Google Scholar
  7. Atkinson, A. B., & Marlier, E. (2010). Living conditions in Europe and the Europe 2020 agenda. Income and living conditions in Europe, 21.Google Scholar
  8. Avgerou, C. (2003). The link between ICT and economic growth in the discourse of development. In M. Korpela, R. Montealegro, & A. Poulymenakou (Eds.), Organizational information systems in the context of globalization (pp. 373–386). Dordrecht, The Netherlands: Kluwer.CrossRefGoogle Scholar
  9. Avgerou, C. (2008). Information systems in developing countries: a critical research review. Journal of Information Technology, 23(3), 133–146.CrossRefGoogle Scholar
  10. Avgerou, C., & Rovere, R. L. (2003). Information systems and the economics of innovation. Edward Elgar Publishing.Google Scholar
  11. Batty, M., Axhausen, K. W., Giannotti, F., Pozdnoukhov, A., Bazzani, A., Wachowicz, M., Ouzounis, G., & Portugali, Y. (2012). Smart cities of the future. The European Physical Journal Special Topics, 214(1), 481–518.CrossRefGoogle Scholar
  12. Bovaird, T. (2007). Beyond engagement and participation: users and community co-production of services. Public Administration Review, 67, 846–860.CrossRefGoogle Scholar
  13. Braga, C. P. (1998). Inclusion or exclusion, Information for Development (InfoDev), The World Bank, http://www.unesco.org/courier/1998_12/uk/dossier/txt21.htm
  14. Bronfman, J. (2014). Beyond Income: A Study of Multidimensional Poverty in Chile.Google Scholar
  15. Castelnovo, W. (2016). Co-production makes cities smarter: citizens’ participation in smart city initiatives. In Co-production in the Public Sector (pp. 97–117). Springer International Publishing.Google Scholar
  16. Chourabi, H., Nam, T., Walker, S., Gil-Garcia, J. R., Mellouli, S., Nahon, K., & Scholl, H. J. (2012). Understanding smart cities: an integrative framework. In System Science (HICSS), 2012 45th Hawaii International Conference on (pp. 2289–2297). IEEE.Google Scholar
  17. Conconi, A., & Ham González, A. (2007). Pobreza multidimensional relativa: Una aplicación a la Argentina. Documentos de Trabajo del CEDLAS.Google Scholar
  18. Connors, J. P., Lei, S., & Kelly, M. (2012). Citizen science in the age of neogeography: utilizing volunteered geographic information for environmental monitoring. Annals of the Association of American Geographers, 102(6), 1267–1289.CrossRefGoogle Scholar
  19. Correa, A. F. (2014). An Individual-centered Approach to Multidimensional Poverty: The Cases of Chile, Colombia, Ecuador and Peru. Maastricht Economic and social Research institute on Innovation and Technology (UNU-MERIT) & Maastricht Graduate School of Governance (MGSoG).Google Scholar
  20. Cruz-Jesus, F., Oliveira, T., & Bacao, F. (2012). Digital divide across the European Union. Information Management, 49(6), 278–291.CrossRefGoogle Scholar
  21. Diga, K., Nwaiwu, F., & Plantinga, P. (2013). ICT policy and poverty reduction in Africa. Info, 15(5), 114–127.CrossRefGoogle Scholar
  22. Doong, S. H., & Ho, S. C. (2012). The impact of ICT development on the global digital divide. Electronic Commerce Research and Applications, 11(5), 518–533.CrossRefGoogle Scholar
  23. Eggleston, K., Jensen, R., Zeckhauser, R. (2002). Information and communication technologies, markets, and economic development. The Global Information Technology Report: readiness for the networked world. Oxford University Press, New York, pp.62–75.Google Scholar
  24. Elwood, S. (2008). Volunteered geographic information: future research directions motivated by critical, participatory, and feminist GIS. GeoJournal, 72(3–4), 173–183.CrossRefGoogle Scholar
  25. Elwood, S., Goodchild, M. F., & Sui, D. Z. (2012). Researching volunteered geographic information: Spatial data, geographic research, and new social practice. Annals of the association of American geographers, 102(3), 571–590.Google Scholar
  26. European Commission (2010). Europe 2020: a strategy for smart, sustainable and inclusive growth, European Commission, Brussels, 2010.Google Scholar
  27. Foster, S. P. (2000). The digital divide: some reflections. The International Information & Library Review, 32(3–4), 437–451.CrossRefGoogle Scholar
  28. Foster, C., & Heeks, R. (2013). Innovation and scaling of ICT for the bottom-of-the-pyramid. Journal of Information Technology, 28(4), 296–315.CrossRefGoogle Scholar
  29. Fusco, A., Guio, A. C., & Marlier, E. (2011). Income poverty and material deprivation in European countries (No. 2011-04). LISER.Google Scholar
  30. Garnham, N. (1997). Amartya Sen’s “capabilities” approach to the evaluation of welfare: Its application to communications. Javnost-The Public, 4(4), 25–34.Google Scholar
  31. Gigler, B. S. (2011). Informational capabilities—the missing link for the impact of ICT on development. Available at SSRN 2191594.Google Scholar
  32. Gigler, B. S. (2015). Development as freedom in a digital age: experiences from the rural poor in Bolivia. World Bank Publications.Google Scholar
  33. Gigler, B. S., & Bailur, S. (Eds.). (2014). Closing the feedback loop: can technology bridge the accountability gap? World Bank Publications.Google Scholar
  34. Goodchild, M. (2007). Citizens as sensors: the world of volunteered geography. GeoJournal, 69, 211–221.CrossRefGoogle Scholar
  35. Goodchild, M. F. (2009). Neogeography and the nature of geographic expertise. Journal of Location Based Services, 3(2), 82–96.CrossRefGoogle Scholar
  36. Graham, S., & Marvin, S. (2001). Splintering urbanism: networked infrastructures, technological mobilities and the urban condition. Psychology Press.Google Scholar
  37. Greenberg, A. (2005). ICTs for poverty alleviation: basic tool and enabling sector.Google Scholar
  38. Guio, A. C. (2009). What can be learned from deprivation indicators in Europe. indicator subgroup of the Social Protection Committee, 10.Google Scholar
  39. Haklay, M. (2010). Geographical citizen science—clash of cultures and new opportunities. In GIScience workshop, 1–6.Google Scholar
  40. Haklay, M. (2013). Citizen science and volunteered geographic information: overview and typology of participation. In D. Z. Sui, S. Elwood, & M. F. Goodchild (Eds.), Crowdsourcing geographic information: volunteered geographic information (VGI) in theory and practice (pp. 105–122). Dordrecht: Springer.CrossRefGoogle Scholar
  41. Hall, J., Matos, S., & Martin, M. (2014). Innovation pathways at the base of the pyramid: establishing technological legitimacy through social attributes. Technovation, 34(5–6), 265–269.CrossRefGoogle Scholar
  42. Harindranath, G., & Sein, M. K. (2007). Revisiting the role of ICT in development. In proceedings of the 9th international conference on social implications of computers in developing countries, São Paulo, Brazil.Google Scholar
  43. Heeks, R. (1999) Information and communication technologies, poverty and development. Development informatics working paper series, Paper No. 5, June 1999, IDPM, Manchester.Google Scholar
  44. Heeks, R. (2008). ICT4D 2.0: the next phase of applying ICT for international development. Computer, 41(6), 26–33.CrossRefGoogle Scholar
  45. Hollands, R. G. (2008). Will the real smart city please stand up? City, 12(3), 303–320.CrossRefGoogle Scholar
  46. Hudson, H. E. (1984). When telephones reach the village: the role of telecommunications in rural development. Norwood: Ablex.Google Scholar
  47. Hudson, H. E. (2001a) ‘Access to the digital economy: issues for rural and developing regions’. Telecommunications Management and Policy Program, University of San Francisco. http://www.usfca.edu/facstaff/hudson/papers/Access%20to%20the%20Digital%20Economy.pdf
  48. Hudson, H. E. (2001b). Telecentre evaluation: issues and strategies. Telecentres: case studies and key issues, 169.Google Scholar
  49. James, J. (2012). The ICT development index and the digital divide: how are they related? Technological Forecasting and Social Change, 79(3), 587–594.CrossRefGoogle Scholar
  50. Khalil, M. A., Dongier, P., D'Costa, V., Zhen-Wei, Q. C., Smith, P. L., Sudan, R., Swanson, E., & Wellenius, B. (2009). 2009 information and communications for development: extending reach and increasing impact. Washington, DC: World Bank Group http://documents.worldbank.org/curated/en/2009/01/10647109/2009-information-communications-development-extending-reach-increasing-impact.Google Scholar
  51. Knudsen, A. S., & Kahlia, M. (2012). Review the role of volunteered geographic information in participatory planning: examples from Denmark and Finland. Perspektiv, 21, 35–48.Google Scholar
  52. Komninos, N. (2004). ‘Regional intelligence: distributed localised information systems for innovation and development’, Int. J. Technology Management, Vol. 28, Nos. 3/4/5/6, pp.483–506.Google Scholar
  53. Komninos, N. (2006). ‘The architecture of intelligent cities’, Intelligent Environments 06, Institution of Engineering and Technology, pp.13–20.Google Scholar
  54. Komninos, N. (2009). Intelligent cities: towards interactive and global innovation environments. International Journal of Innovation and Regional Development, 1(4), 337–355.Google Scholar
  55. Komninos, N. (2013). Social innovation in smart cities: applications, drivers of intelligence, and governance. Paper presented at the conference “Social Innovations and Conflicts in Urban Development and Planning”, Leibniz Institute for Regional Development and Structural Planning (IRS), Berlin, 7–8 November 2013.Google Scholar
  56. Komninos, Ν. (2014). The age of intelligent cities. London and New York: Routledge.Google Scholar
  57. Komninos N., Kakderi C. and Tsarchopoulos P. (2014). New services design for smart cities: a planning road-map for user-driven innovation. Proceedings of the 2014 ACM international workshop on wireless and mobile technologies for smart cities (WiMobCity ‘14): pp.29–39, Academic OneFile database.  https://doi.org/10.1145/2633661.2633664.
  58. Komninos, N., Bratsas, C., Kakderi, C., & Tsarchopoulos, P. (2015). Smart City Ontologies: Improving the effectiveness of smart city applications. Journal of Smart Cities, 1(1).Google Scholar
  59. Kuhn, W. (2007). Volunteered Geographic Information and GIScience. NCGIA, UC Santa Barbara, 13–14 December, 2007.Google Scholar
  60. Kyriakidou, V., Michalakelis, C., & Sphicopoulos, T. (2011). Digital divide gap convergence in Europe. Technology in Society, 33(3), 265–270.CrossRefGoogle Scholar
  61. Linders, D. (2012). From e-government to we-government: defining a typology for citizen coproduction in the age of social media. Government Information Quarterly, 29(4), 446–454.CrossRefGoogle Scholar
  62. Loh, Y. A. (2015). Approaches to ICT for development (ICT4D): vulnerabilities vs. capabilities. Information Development, 31(3), 229–238.CrossRefGoogle Scholar
  63. Madej, M., M. Soniat, L. Dupont, and M. M. Thompson. (2012). Assessing street conditions through volunteer spatial mapping in lakeview assessing street conditions through volunteer spatial mapping in lakeview. Planning and Urban Studies Reports and Presentations.Google Scholar
  64. Madon, S. (2000), “The Internet and socio-economic development: exploring the interaction.” Information Technology and People 13.Google Scholar
  65. Madon, S. (2008). Evaluating the developmental impact of e-governance initiatives: An exploratory framework. ICTs and Indian Social Change: Diffusion, Poverty, Governance, 268.Google Scholar
  66. Mansell, R. (1999). Information and communication technologies for development: assessing the potential and the risks. Telecommunications Policy, 23, 35–50.CrossRefGoogle Scholar
  67. Mansell, R. (2002). From digital divides to digital entitlements in knowledge societies. Current sociology, 50(3), 407–426.Google Scholar
  68. Mansell, R. and When, U. (1998), Knowledge societies: information technology for sustainable development, Oxford University Press.Google Scholar
  69. Moseson, A. J., Lama, L., & Tangorra, J. (2015). Development by technology seeding. Journal of International Development, 27(4), 489–503.CrossRefGoogle Scholar
  70. Nam, T. (2012). Suggesting frameworks of citizen-sourcing via Government 2.0. Government Information Quarterly, 29(1), 12–20.CrossRefGoogle Scholar
  71. Nelson, R. R., & Winter, S. G. (1982). The Schumpeterian tradeoff revisited. The American Economic Review, 72(1), 114–132.Google Scholar
  72. OECD. (2011), OECD guide to measuring the information society 2011, OECD Publishing, Paris. doi:  https://doi.org/10.1787/9789264113541-en
  73. Panori, A. (2017). A tale of hidden cities. REGION, 4(3), 19–38.  10.18335/region.v4i3.189.CrossRefGoogle Scholar
  74. Panori, A., Ballas, D., & Psycharis, Y. (2017). SimAthens: a spatial microsimulation approach to the estimation and analysis of small area income distributions and poverty rates in the city of Athens, Greece. Computers, Environment and Urban Systems, 63, 15–25.CrossRefGoogle Scholar
  75. Parr, D. A. (2015). The production of volunteered geographic information: a study of OpenStreetMap in the United States (Doctoral dissertation, Texas State University).Google Scholar
  76. Pigato, M. A. (2001) ‘Information and communication technology, poverty, and development in sub-Saharan Africa and South Asia’. Africa Region Working Paper Series No. 20, August 2001. The World Bank. http://www.worldbank.org/afr/wps/wp20.h
  77. Prahalad, C. K., McCracken, P., & McCracken, R. (2009). The new nature of innovation. Copenhagen: Reportfor OECD, FORA.Google Scholar
  78. Ramani, S., & Mukherjee, V. (2014). Can breakthrough innovations serve the poor (bop) and create reputational (CSR) value? Indian case studies. Technovation, 35(5–6), 295–305.CrossRefGoogle Scholar
  79. Rippin, N. (2016). Multidimensional Poverty in Germany: A Capability Approach. In Forum for Social Economics (Vol. 45, No. 2-3, pp. 230-255). Routledge.Google Scholar
  80. Schaffers, H., Komninos, N., Pallot, M., Trousse, B., Nilsson, M., & Oliveira, A. (2011). Smart cities and the future internet: towards cooperation frameworks for open innovation. In The Future Internet Assembly (pp. 431–446). Springer Berlin Heidelberg.Google Scholar
  81. Schumpeter, J. A. (1939). Business cycles: a theoretical, historical and statistical analysis of the capitalist process. New York: McGraw-Hill.Google Scholar
  82. Schumpeter, J. A. (1947). The creative response in economic history. The Journal of Economic History, 7(2), 149–159.CrossRefGoogle Scholar
  83. Schuurman, D., Baccarne, B., De Marez, L., & Mechant, P. (2012). Smart ideas for smart cities: investigating crowdsourcing for generating and selecting ideas for ICT innovation in a city context. Journal of Theoretical and Applied Electronic Commerce Research, 7(3), 49–62.CrossRefGoogle Scholar
  84. Seegolam, A., Sukhoo, A., & Bhoyroo, V. (2015). ICT as an enabler to achieve sustainable development goals for developing countries: a proposed assessment approach. In eChallenges e-2015 Conference (pp. 1–11). IEEE.Google Scholar
  85. Sen, A. (1985). Well-being, agency and freedom: the Dewey lectures 1984. The Journal of Philosophy, 82(4), 169–221.Google Scholar
  86. Sen, A. (1992). Inequality reexamined. Clarendon Press.Google Scholar
  87. Sen, A. (1993). Capability and well-being73. The quality of life, 30.Google Scholar
  88. Sen, A. (1997). Editorial: Human capital and human capability. World Development, 25, 1959–1961.CrossRefGoogle Scholar
  89. Sen, A. (1999). Development as freedom. New York: Knopf Press.Google Scholar
  90. Silvestre, B., & Silva Neto, R. (2014). Capability accumulation, innovation, and technology diffusion: lessons from a base of the pyramid cluster. Technovation, 34(5–6), 270–283.CrossRefGoogle Scholar
  91. Song, W., and G. Sun. (2010). The role of mobile volunteered geographic information in urban management. In 2010 18th International Conference on Geoinformatics. Beijing, China: IEEE.Google Scholar
  92. Suppa, N. (2015). Towards a multidimensional poverty index for Germany.Google Scholar
  93. Townsend, A. M. (2013). Smart cities: big data, civic hackers, and the quest for a new utopia. WW Norton & Company.Google Scholar
  94. Tulloch, D. L. (2008). Is VGI participation? From vernal pools to video games. GeoJournal, 72(3–4), 161–171.CrossRefGoogle Scholar
  95. UN (2015a). The Millennium Development Goals Report 2015, United Nations.Google Scholar
  96. UN (2015b). Transforming our world: the 2030 agenda for sustainable development, United Nations.Google Scholar
  97. UN (2016a). Leaving no one behind: progress towards achieving socially-inclusive development. Report on the World Social Situation 2016, United Nations.Google Scholar
  98. UN (2016b). Draft outcome document of the United Nations Conference on Housing and Sustainable Urban Development (Habitat III), United Nations, September 2016.Google Scholar
  99. UN-Habitat (2016). Urbanization and development: emerging futures. World Cities Report 2016, United Nations.Google Scholar
  100. Weziak-Bialowolska, D. (2016). Spatial Variation in EU Poverty with Respect to Health, Education and Living Standards. Social indicators research, 125(2), 451–479.Google Scholar
  101. Whelan, Christopher T., Nolan, Brian. and Maitre, Bertrand, (2014), Multidimensional Poverty Measurement in Europe: An Application of the Adjusted Headcount Approach, Journal of European Social Policy, 24(2), 183–197.Google Scholar
  102. Wresch, W. (1996). Disconnected: haves and have-nots in the information age. New Brunswick: Rutgers University Press.Google Scholar
  103. Yildirim, N., & Ansal, H. (2011). Foresighting FLOSS (free/libre/opensourcesoftware) from a developing country perspective: the case of Turkey. Technovation, 31, 666–678.Google Scholar

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Authors and Affiliations

  1. 1.URENIO ResearchAristotle University of ThessalonikiThessalonikiGreece

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