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Data-driven smart sustainable urbanism: the intertwined societal factors underlying its materialization, success, expansion, and evolution

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Abstract

Visions of future advances in science and technology (S&T) inevitably bring with them wide-ranging common visions on how societies, and thus cities as social organizations, will evolve in the future and the immense opportunities this future will bring. This relates to the role of science-based technology in modern society. The focus here is on big data science and analytics and the underpinning technologies as an instance of S&T and its role in advancing sustainability in modern cities. This relates to what has been dubbed data-driven smart sustainable urbanism. However, there is a little understanding about how it has emerged and why it has become institutionalized and interwoven with politics and policy—urban dissemination. Therefore, this paper examines the intertwined societal factors underlying its materialization, success, expansion, and evolution, as well as critically discusses urban science and big data technology as social constructions in terms of their inherent flaws, limits, and biases. This paper argues that data-driven smart sustainable urbanism is shaped by socio-cultural and politico-institutional structures. And it will prevail for many years to come given the underlying transformational power of big data science and analytics, coupled with its legitimation capacity associated with the scientific discourse as the ultimate form of rational thought and the basis for legitimacy in knowledge-making and policy-making. This paper also argues that there is a need for re-casting urban science in ways that reconfigure the underlying epistemology to recognize the complex and dynamic nature of smart sustainable cities, as well as for re-casting them in ways that re-orientate in how they are conceived.

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References

  • Ahvenniemi, H., Huovila, A., Pinto-Seppä, I., & Airaksinen, M. (2017). What are the differences between sustainable and smart cities? Cities, 60, 234–245.

    Google Scholar 

  • Al Nuaimi, E., Al Neyadi, H., Nader, M., & Al-Jaroodi, J. (2015). Applications of big data to smart cities. Journal of Internet Services and Applications, 6(25), 1–15.

    Google Scholar 

  • Anderson, C. (2008). The end of theory: The data deluge makes the scientific method obsolete. Wired, 23 June 2008. http://www.wired.com/science/discoveries/magazine/16–07/pb_theo–ry. Accessed Oct 12, 2012.

  • Angelidou, M., Artemis, P., Nicos, K., Christina, K., Tsarchopoulos, P., & Anastasia, P. (2017). Enhancing sustainable urban development through smart city applications. Journal of Science and Technology Policy Management, 9, 1–25.

    Google Scholar 

  • Aseem, I. (2013). Designing urban transformation. New York: Routledge.

    Google Scholar 

  • Baghramian, M. (2004). Relativism. New York: Routledge.

    Google Scholar 

  • Batty, M. (2013). Big data, smart cities and city planning. Dialogues in Human Geography, 3(3), 274–279.

    Google Scholar 

  • Batty, M., Axhausen, K. W., Giannotti, F., Pozdnoukhov, A., Bazzani, A., Wachowicz, M., et al. (2012). Smart cities of the future. The European Physical Journal, 214, 481–518.

    Google Scholar 

  • Bettencourt, L. M. A. (2014). The uses of big data in cities. Santa Fe: Santa Fe Institute.

    Google Scholar 

  • Biagioli, M. (Ed.). (1999). The science studies reader. London: Routledge.

    Google Scholar 

  • Bibri, S. E. (2015). The shaping of ambient intelligence and the internet of things: Historico-epistemic, socio-cultural, politico-institutional and eco-environmental dimensions. Berlin: Springer.

    Google Scholar 

  • Bibri, S. E. (2018a). Smart sustainable cities of the future: The untapped potential of big data analytics and context aware computing for advancing sustainability. Berlin: Springer.

    Google Scholar 

  • Bibri, S. E. (2018b). The IoT for smart sustainable cities of the future: An analytical framework for sensor-based big data applications for environmental sustainability. Sustainable Cities and Society, 38, 230–253.

    Google Scholar 

  • Bibri, S. E. (2019a). On the sustainability of smart and smarter cities and related big data applications: An interdisciplinary and transdisciplinary review and synthesis. Journal of Big Data, 6, 25.

    Google Scholar 

  • Bibri, S. E. (2019b). Big data science and analytics for smart sustainable urbanism: Unprecedented paradigmatic shifts and practical advancements. Berlin: Springer.

    Google Scholar 

  • Bibri, S. E. (2019c). The sciences underlying smart sustainable urbanism: Unprecedented paradigmatic and scholarly shifts in light of big data science and analytics. Smart Cities, 2(2), 179–213.

    Google Scholar 

  • Bibri, S. E. (2019d). The anatomy of the data-driven smart sustainable city: instrumentation, datafication, computerization and related applications. Journal of Big Data, 6, 59. (in press).

    Google Scholar 

  • Bibri, S. E., & Krogstie, J. (2016). On the social shaping dimensions of smart sustainable cities: A study in science, technology, and society. Sustainable Cities and Society, 29, 219–246.

    Google Scholar 

  • Bibri, S. E., & Krogstie, J. (2017a). Smart sustainable cities of the future: An extensive interdisciplinary literature review. Sustainable Cities and Society, 31, 183–212.

    Google Scholar 

  • Bibri, S. E., & Krogstie, J. (2017b). ICT of the new wave of computing for sustainable urban forms: Their big data and context-aware augmented typologies and design concepts. Sustainable Cities and Society, 32, 449–474.

    Google Scholar 

  • Bibri, S. E., & Krogstie, J. (2018). The big data deluge for transforming the knowledge of smart sustainable cities: A data mining framework for urban analytics. In Proceedings of the 3rd annual international conference on smart city applications, ACM, Oct 11–12, Tetouan, Morocco.

  • Bibri, S. E., & Krogstie, J. (2019). A novel model for smart sustainable city of the future: A scholarly and planning approach to its analysis, investigation, and development. Journal of FS (in press).

  • Boeing, G., Church, D., Hubbard, H., Mickens, J., & Rudis, L. (2014). LEED-ND and livability revisited. Berkeley Planning Journal, 27(1), 31–55.

    Google Scholar 

  • Bowker, G. (2005). Memory practices in the sciences. Cambridge: MIT Press.

    Google Scholar 

  • Bulkeley, H., & Betsill, M. (2005). Rethinking sustainable cities: multilevel governance and the “urban” politics of climate change. Environmental Politics, 14(1), 42–63.

    Google Scholar 

  • Burr, V. (1995). An introduction to social constructivism. London: Sage.

    Google Scholar 

  • Buttimer, A. (1976). Grasping the dynamism of lifeworld. Annals of the Association of American Geographers, 66, 277–292.

    Google Scholar 

  • Crawford, K., & Schultz, J. (2014). Big data and due process: Toward a framework to redress predictive privacy harms. Boston College Law Review, 55, 93–128.

    Google Scholar 

  • Cukier, K., & Mayer-Schoenberger, V. (2013). The rise of big data. Foreign Affairs, 92(3), 28–40.

    Google Scholar 

  • Dawkins, R. (2016). The God delusion. 10th anniversary edition (with new introduction by Richard Dawkins and afterword by Daniel Dennett), Black Swan.

  • Dodge, M., & Kitchin, R. (2007). The automatic management of drivers and driving spaces. Geoforum, 38(2), 264–275.

    Google Scholar 

  • Flood, J. (2011). The fires: How a computer formula, big ideas, and the best of intentions burned down New York city—And determined the future of cities. New York, NY.

  • Foth, M. (2009). Handbook of research on urban informatics: The practice and promise of the real-time city. Hershey: Information Science Reference.

    Google Scholar 

  • Foucault, M. (1972). The archaeology of knowledge. London: Routledge.

    Google Scholar 

  • Foucault, M. (1977). Discipline and punish: The birth of the prison. New York: Pantheon Books.

    Google Scholar 

  • Foucault, M. (1980). Truth and power. In C. Gordon (Ed.), Power/knowledge, selected interviews and writings 1972–1977. Hemel Hempstead: Harvester Wheatsheaf.

    Google Scholar 

  • Gergen, K. (1985). The social constructionist movement in modern social psychology. American Psychologist, 40(3), 266–275.

    Google Scholar 

  • Gitelman, L. (Ed.). (2013). “Raw data” is an oxymoron. Cambridge: MIT Press.

    Google Scholar 

  • Greenfield, A. (2013). Against the smart city. New York, NY: Do Publications.

    Google Scholar 

  • Hajer, M. A. (1995). The politics of environmental discourse: Ecological modernization and the policy process. Oxford: Clarendon Press.

    Google Scholar 

  • Harvey, D. (1973/2009). Social justice and the city. London: Edward Arnold.

  • Hashem, I. A. T., Chang, V., Anuar, N. B., Adewole, K., Yaqoob, I., Gani, A., et al. (2016). The role of big data in smart city. International Journal of Information Management, 36, 748–758.

    Google Scholar 

  • Heidegger, M. (1962). Being and time. New York: Harper & Row.

    Google Scholar 

  • Hess, D. J. (1997). Science studies: An advanced introduction. New York: New York University Press.

    Google Scholar 

  • Hollands, R. G. (2008). Will the real smart city please stand up? City anal urban trends cult theory. Policy Action, 12(3), 303–320.

    Google Scholar 

  • Jasanoff, S., Markle, G., Petersen, J., & Pinch, T. (Eds.). (1995). Handbook of science and technology studies. Thousand Oaks: Sage Publications.

    Google Scholar 

  • Jessop, R. (1998). The narrative of enterprise and the enterprise of narrative: place marketing and the entrepreneurial city. In T. H. All & P. Hubbard (Eds.), The entrepreneurial city: geographies of politics, regime and representation (pp. 77–99). Chichester: Wiley.

    Google Scholar 

  • Keith, D. (1977). Is cultural relativism self-refuting? British Journal of Sociology, 28(1).

  • Kelling, S., Hochachka, W., Fink, D., Riedewald, M., Caruana, R., Ballard, G., et al. (2009). Data-intensive science: A new paradigm for biodiversity studies. BioScience, 59, 613–620.

    Google Scholar 

  • Khanac, Z., Pervaiz, Z., & Abbasi, A. G. (2017). Towards a secure service provisioning framework in a smart city environment. Future Generation Computer Systems, 77, 112–135.

    Google Scholar 

  • Kitchin, R. (2014a). The real-time city? Big data and smart urbanism. GeoJournal, 79, 1–14.

    Google Scholar 

  • Kitchin, R. (2014b). The data revolution: Big data, open data, data infrastructures and their consequences. London: Sage.

    Google Scholar 

  • Kitchin, R. (2015a). Data-driven, networked urbanism. https://doi.org/10.2139/ssrn.2641802.

  • Kitchin, R. (2015b). Making sense of smart cities: Addressing present shortcomings. Cambridge Journal of Regions, Economy and Society, 8(1), 131–136. https://doi.org/10.1093/cjres/rsu027.

    Article  Google Scholar 

  • Kitchin, R. (2016a). The ethics of smart cities and urban science. Philosophical Transactions of the Royal Society A, 374, 20160115.

    Google Scholar 

  • Kitchin, R. (2016b). Reframing, reimagining and remaking smart cities. The programmable city working paper 20.

  • Kitchin, R., Coletta, C., Evans, L., Heaphy, L., & MacDonncha, D. (2017). Smart cities, urban technocrats, epistemic communities and advocacy coalitions. The programmable city working paper 26. http://progcity.maynoothuniversity.ie/2017/03/new–paper–smart–cities–urban–technocrats–epistemic–communities–and–advocacy–coalitions/. Accessed 17 May 2019.

  • Kitchin, R., & Dodge, M. (2011). Code/space: Software and everyday life. Cambridge: MIT Press.

    Google Scholar 

  • Kitchin, R., Lauriault, T. P., & McArdle, G. (2015). Knowing and governing cities through urban indicators, city benchmarking & real-time dashboards. Regional Studies Regional Science, 2, 1–28.

    Google Scholar 

  • Kourtit, K., Nijkamp, P., & Arribas-Bel, D. (2012). Smart cities perspective—A comparative European study by means of self-organizing maps. Innovation, 25(2), 229–246.

    Google Scholar 

  • Kramers, A., Höjer, M., Lövehagen, N., & Wangel, J. (2014). Smart sustainable cities: Exploring ICT solutions for reduced energy use in cities. Environmental Modelling and Software, 56, 52–62.

    Google Scholar 

  • Kuhn, T. S. (1962). The structure of scientific revolutions. Chicago: University of Chicago Press.

    Google Scholar 

  • Larice, M., & MacDonald, E. (Eds.). (2007). The urban design reader. New York: Routledge.

    Google Scholar 

  • Lazer, D., Pentland, A., Adamic, L., Aral, S., Barabasi, A. L., Brewer, D., et al. (2009). Computational social science. Science, 323, 721–733. https://doi.org/10.1126/science.1167742.

    Article  Google Scholar 

  • Miller, H. J. (2010). The data avalanche is here. Shouldn’t we be digging? Journal of Regional Science, 50, 181–201.

    Google Scholar 

  • Pantelis, K., & Aija, L. (2013). Understanding the value of (big) data. In Big Data 2013 IEEE international conference on IEEE, pp. 38–42

  • Parsons, W. (2004). Not just steering but weaving: Relevant knowledge and the craft of building policy capacity and coherence. Australian Journal of Public Administration, 63, 43–57.

    Google Scholar 

  • Popper, K. (1957/1986). The poverty of historicism. London: Ark paperbacks.

  • Rathore, M. M., Won-HwaHong, A. P., Seo, H. C., Awan, I., & Saeed, S. (2018). Exploiting IoT and big data analytics: Defining smart digital city using real-time urban data. Sustainable Cities and Society, 40, 600–610.

    Google Scholar 

  • Ratti, C., & Offenhuber, D. (2014). Decoding the city: How big data can change urbanism. Basel: Birkhauser Verlag AG.

    Google Scholar 

  • Ribes, D., & Jackson, S. J. (2013). Data bite man: The work of sustaining long-term study. In L. Gitelman (Ed.), ‘Raw data’ is an oxymoron (pp. 147–166). Cambridge: MIT Press.

    Google Scholar 

  • Rivera, M. B., Eriksson, E., & Wangel, J. (2015). ICT practices in smart sustainable cities—In the intersection of technological solutions and practices of everyday life. In 29th international conference on informatics for environmental protection (EnviroInfo 2015), third international conference on ICT for sustainability (ICT4S 2015) (pp. 317–324). Atlantis Press.

  • Rotmans, J., Kemp, R., & van Asselt, M. (2001). More evolution than revolution: Transition management in public policy. Foresight, 3(1), 15–31.

    Google Scholar 

  • Schmidt, V. (2008). Discursive institutionalism: The explanatory power of ideas and discourse. Annual Review of Political Science, 11, 303–326.

    Google Scholar 

  • Shahrokni, H., Årman, L., Lazarevic, D., Nilsson, A., & Brandt, N. (2015). Implementing smart urban metabolism in the Stockholm Royal Seaport: Smart city SRS. Journal of Industrial Ecology, 19(5), 917–929.

    Google Scholar 

  • Sismondo, S. (2003). An introduction to science and technology studies. Oxford: Blackwell.

    Google Scholar 

  • Smith, A. (2003). Transforming technological regimes for sustainable development: A role for alternative technology niches? Science and Public Policy, 30(2), 127–135.

    Google Scholar 

  • Strandberg, K. L. (2014). Monitoring, datafication and consent: Legal approaches to privacy in the big data context. In J. Lane, V. Stodden, S. Bender, & H. Nissenbaum (Eds.), Privacy, big data and the public good (pp. 5–43). Cambridge: Cambridge University Press.

    Google Scholar 

  • Townsend, A. (2013). Smart cities—Big data, civic hackers and the quest for a new utopia. New York: Norton & Company.

    Google Scholar 

  • Williams, K. (2009). Sustainable cities: Research and practice challenges. International Journal of Urban Sustainable Development, 1(1), 128–132.

    Google Scholar 

  • Yigitcanlar, T., & Lee, S. H. (2013). Korean ubiquitous-eco-city: A smart-sustainable urban form or a branding hoax? Technological Forecasting and Social Change, 89, 100–114.

    Google Scholar 

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Bibri, S.E. Data-driven smart sustainable urbanism: the intertwined societal factors underlying its materialization, success, expansion, and evolution. GeoJournal 86, 43–68 (2021). https://doi.org/10.1007/s10708-019-10061-x

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