Big, Thick, Small and Short - The Flaws of Current Urban Big Data Trends: A Viewpoint
The last decade of the 20th century, as the internet emerged, saw a data revolution. Relatively cheap digital storage and over 1.5 billion gigabytes of available data that could now be used. This also created new challenges; new types of data, coined in 2001 as “Big Data” (due to its three-dimensional characteristics): Volume, Velocity and Variety (Laney, 2001), has to be managed differently. Many cities and city planners hailed the new revolution as the ultimate solution for urban problems. Unfortunately, there is little evidence that data centered cities are succeeding in overcoming urban challenges. In fact, there is a growing understanding that in order to infuse data centered decision making, specifically in urban planning, new models and processes, designed by and for cities are needed. This article examines the origins and the evolution of current Big Data and Smart City trends, from the development of Forrester's System Dynamic Model, through the emergence of the data corporations and the introduction of the Smart City Model. The analysis depicts how the Big Data actors determine the framing of urban data utilization and alternate ways of collecting and utilizing data for urban management and planning, more in tune to the needs and features of cities in the 21st century.
-----. (1995b) Urban dynamics-The first fifty years, System Dynamics Review, 11, 3: 204.
Anderson, C. (2008) The end of theory: The data deluge makes the scientific method obsolete, Wired, 06.23.08.
Ang, Yuen Yuen (2019) Integrating big data and thick data to transform public services delivery. IBM Centre for Business Government
Flood, J. (2010) Why the Bronx burned, New York Post, https://nypost.com/2010/05/16/why-the-bronx-burned/
Forrester, J. W. (1969) Urban Dynamics. Waltham: Pegasus Communications.
-----. (1971) Counterintuitive behavior of social systems. Technology Review, 73, 3: 52-68.
-----. (1978) Industrial Dynamics: A Major Breakthrough for Decision Makers. Cambridge, Mass.: The MIT Press
-----. (1989) The beginning of system dynamics. Banquet Talk at the International Meeting of the System Dynamics Society Stuttgart, Germany July 13, l989
-----. (1993) System Dynamics and the Lessons of 35 Years. In Kenyon B. De Greene (ed.) Systems-Based Approach to Policy-making. Norwell, MA: Kluwer Academic Publishers, 1993, 1-36.
IBM (no date), Smarter Planet, https://www.ibm.com/ibm/history/ibm100/us/en/icons/smarterplanet/
IBM (2011) IBM Smarter City: Portland, Oregon clip transcript, www.youtube.com/watch?v=uBYsSFbBeR4
IBM (2011) Press release: IBM and city of Portland collaborate to build a smarter city, https://www.prnewswire.com/news-releases/ibm-and-city-of-portland-collaborate-to-build-a-smarter-city-127298003.html
Laney, D. (2001) 3D Data Management: Controlling Data Volume, Velocity and Variety. META Group Research Note, 6. https://blogs.gartner.com/doug-laney/files/2012/01/ad949-3D-Data-Management-Controlling-Data-Volume-Velocity-and-Variety.pdf
Lindsay G. (2011) IBM Partners with Portland to Play SimCity For Real, Fast Company, 08-08-11, https://www.fastcompany.com/1678375/ibm-partners-with-portland-to-play-simcity-for-real
Lindstrom, M. (2016) Small Data: The Tiny Clues that Uncover Huge Trends. New York St. Martin's Press.
Los Angeles Community Analysis Bureau (1974) State of the city ii: A cluster analysis of Los Angeles, City of Los Angeles.
Municipality of Copenhagen (2018) City Data Exchange – Lessons Learned from a Public/Private Data Collaboration, https://cphsolutionslab.dk/media/site/1837671186-1601734920/city-data-exchange-cde-lessons-learned-from-a-public-private-data-collaboration.pdf
Rijmenam, M. van. (2013) Why The 3V’s Are Not Sufficient to Describe Big Data, Datafloq.https://datafloq.com/read/3vs-sufficient-describe-big-data/166
Starr, P. (1994) Seductions of Sim: Policy as a simulation game. The American Prospect, 17: 19-29
Townsend, A. M. (2013) Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia. New York: W. W. Norton & Company.
Sicular, S. (2013) Gartner’s Big Data Definition Consists of Three Parts, Not to Be Confused with Three “V”s, Gartner Blogs. https://blogs.gartner.com/svetlana-sicular/gartners-big-data-definition-consists-of-three-parts-not-to-be-confused-with-three-vs/
Vallianatos, M. (2015) Uncovering the Early History of “Big Data” and the “Smart City” in Los Angeles, Boom California, https://boomcalifornia.org/2015/06/16/uncovering-the-early-history-of-big-data-and-the-smart-city-in-la/
Wang, T. (2013) Big data needs thick data, Ethnography Matters, 13, https://medium.com/ethnography-matters/why-big-data-needs-thick-data-b4b3e75e3d7
World Bank (2017) Big data in action for government: Big data innovation in public services, policy, and engagement, http://hdl.handle.net/10986/26391
- The contributor(s) (authors) warrant that the entire work is original and unpublished; it is submitted only to this Journal and all text, data, figures/tables or other illustrations included in this work are completely original and unpublished, and these have not been previously published or submitted elsewhere in any form or media whatsoever.
- The contributor(s) warrant that the work contains no unlawful or libelous statements and opinions and liable materials of any kind whatsoever, does not infringe on any copyrights, intellectual property rights, personal rights or rights of any kind of others, nor contains any plagiarized, fraudulent, improperly attributed materials, instructions, procedures, information or ideas that might cause any harm, damage, injury, losses or costs of any kind to person or property.
- The contributor(s) retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- The contributor(s) are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- The contributor(s) are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
- Geography Research Forum may disseminate the content of the publications and publications’ Meta data in text, image, or other print and electronic formats to providers of research databases (e.g. EBSCO, GeoBase, JSTOR) to facilitate publications' exposure.