Can Smart City Data be Used to Create New Official Statistics?

ANSI 2016. Directory of Smart and Sustainable Cities Standardization Initiatives and Related Activities. American National Standards Institute Network on Smart and Sustainable Cities (ANSSC). Available at: https://www.ansi.org/standards_activities/-standards_boards_panels/anssc/overview#Standards (accessed February 2021).Search in Google Scholar

Bradshaw, R. 2019. “Instrumentalization in the Public Smart Bikeshare Sector.” PhD Doctoral thesis, Maynooth University. Available at: http://mural.maynoothuniversity.ie/10509/ (accessed February 2021).Search in Google Scholar

Celikoglu, H.B. 2013. “An approach to dynamic classification of traffic flow patterns.” Computer-Aided Civil and Infrastructure Engineering; 28, 4: 273–288. DOI: doi.org/10.1111/j.1467-8667.2012.00792.x.10.1111/j.1467-8667.2012.00792.xSearch in Google Scholar

ECOSOC. 2015. Report of the Global Working Group on Big data for official statistics. United National Economic and Social Council. 46th Statistical Commission. Available at: http://unstats.un.org/unsd/statcom/doc15/2015-4-BigData.pdf (accessed February 2021).Search in Google Scholar

ESSC. 2013. The Scheveningen Memorandum on Big Data and Official Statistics. Scheveningen: Directors General of the National Statistical Institutes (DGINS). Available at: https://ec.europa.eu/eurostat/cros/system/files/SCHEVENINGEN_MEMORANDUM%20Final%20version.pdf. (accessed February 2021).Search in Google Scholar

ESSC. 2014. “ESS Big Data Action Plan and Roadmap 1.0.” Riga: European Statistical System Committee. 26th September 2014, Riga. Latvia. Available at: https://ec.europa.eu/eurostat/cros/content/ess-big-data-action-plan-and-roadmap-10_en (accessed February 2021)Search in Google Scholar

ESSC. 2018. “The Bucharest Memorandum on Official Statistics in a Datafied Society (Trusted Smart Statistics).” Bucharest: Directors General of the National Statistics Institutes (DGINS), 12th October 2018, Bucharest, Bulgaria. Available at: https://ec.europa.eu/eurostat/documents/7330775/7339482/The þ Bucharest þ Memorandum þ on þ Trusted þ Smart þ Statistics þ FINAL.pdf (accessed February 2021).Search in Google Scholar

European Union. 2008. “Directive 2008/50/EC of the European Parliament and of the Council of 21 May 2008 on ambient air quality and cleaner air for Europe.” Official Journal of the European Union 51: 1–44. Available at: https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32008L0050&from=EN (accessed February 2021).Search in Google Scholar

Eurostat. 2014a. Accreditation procedure for statistical data from non-official sources. European Commission. Available at: https://ec.europa.eu/eurostat/cros/system/files/-D5_Accreditation%20procedure%20for%20statistical%20data%20from%20nonofficial%20sources_20140206_0.pdf (accessed February 2021).Search in Google Scholar

Eurostat. 2014b. “Big data – an opportunity or a threat to official statistics?” Paper presented at the Conference of European Statisticians, 62nd plenary session, Paris, 9 – 11 April, 2014. Available at: http://www.unece.org/fileadmin/DAM/stats/documents/ece/ces/2014/32-Eurostat-Big_Data.pdf (accessed February 2021).Search in Google Scholar

Eurostat. 2018. Report describing the quality aspects of Big Data for Official Statistics. ESSnet Big Data, Work Package 8, Deliverable 8.2. Available at: https://ec.europa.eu/eurostat/cros/sites/crosportal/files/WP8_Deliverable_8.2_Quality_aspects.pdf (accessed February 2021).Search in Google Scholar

Florescu, D., M. Karlberg, F. Reis, P.R. Del Castillo, M. Skaliotis, and A. Wirthmann. 2014. “Will ‘big data’ transform official statistics?” European Conference on the Quality of Official Statistics. Available at: http://www.q2014.at/fileadmin/user_upload/ESTAT-Q2014-BigDataOS-v1a.pdf (accessed February 2021).Search in Google Scholar

Karvonen, A., F. Cugurullo, and F. Caprotti. 2018. Inside Smart Cities: Place, Politics and Urban Innovation. London: Routledge.10.4324/9781351166201Search in Google Scholar

Kahn, J., M. Ketzel, K. Kakosimos M. Sorensen, and S.S. Jensen. 2018. “Road traffic air and noise pollution exposure assessment – A review of tools and techniques.” Science of The Total Environment 634 no. 1: 661–676. DOI: https://doi.org/10.1016/j.scitotenv.2018.03.374.10.1016/j.scitotenv.2018.03.37429642048Search in Google Scholar

Kitchin, R. 2015. “The Opportunities, Challenges and Risks of Big Data for Official Statistics.” Statistical Journal of the International Association of Official Statistics 31. 3: 471–481. DOI: https://doi.org/10.3233/SJI-150906.10.3233/SJI-150906Search in Google Scholar

Kitchin, R. 2016. Getting smarter about smart cities: Improving data privacy and data security. Data Protection Unit, Department of the Taoiseach, Dublin, Ireland. Available at: http://mural.maynoothuniversity.ie/7242/1/Smart (accessed February 2021).Search in Google Scholar

Kitchin, R. 2017. “Data-Driven Urbanism”. In: Data and the City. Kitchin R., G. McArdle, T. Lauriault, eds.: 44–56. Routledge: London.10.4324/9781315407388-4Search in Google Scholar

Kitchin, R, T. Lauriault, and G. McArdle. 2015. “Knowing and governing cities through urban indicators, city benchmarking and real-time dashboards.” Regional Studies, Regional Science 2: 1–28. DOI: https://doi.org/10.1080/21681376.2014.983149.10.1080/21681376.2014.983149Search in Google Scholar

Kitchin, R., and G. McArdle. 2016. “What makes Big Data, Big Data? Exploring the ontological characteristics of 26 datasets.” Big Data and Society 3: 1–10. DOI: https://doi.org/10.1177/2053951716631130.10.1177/2053951716631130Search in Google Scholar

Landefeld, S. 2014. “Uses of Big Data for Official Statistics: Privacy, Incentives, Statistical Challenges, and Other Issues.” Paper presented at International Conference on Big Data for Official Statistics, 28–30 October 2014, Beijing, China. Available at: https://unstats.un.org/unsd/trade/events/2014/beijing/Steve%20Landefeld%20-%20Uses%20of%20Big%20Data%20for%20official%20statistics.pdf (accessed February 2021).Search in Google Scholar

MacFeely, S. 2018. “The privacy dilemma for official statistics in a big data world.” Open Access Biostatistics and Bioinformatics 2. 1: 1:3. DOI: https://doi.org/10.31031/OABB.2018.02.000526.10.31031/OABB.2018.02.000526Search in Google Scholar

McArdle, G, and R. Kitchin. 2016. “Improving the Veracity of Open and Real-Time Urban Data.” Built Environment 42, 3: 446–462. DOI: https://doi.org/10.2148/benv.42.3.457.10.2148/benv.42.3.457Search in Google Scholar

OAG. 2019. Defining Late: is 15 minutes the right measure? Official Aviation Guide, Worldwide Aviation Limited. Available at: https://www.oag.com/hubfs/Defining_Late/Defining-Late-Report.pdf?hsLang=en-gb (accessed February 2021).Search in Google Scholar

OECD. 2011. Quality Framework and Guidelines for OECD Statistical Activities. Organisation for Economic Co-operation and Development, Statistics Directorate. Available at: https://www.oecd.org/sdd/qualityframeworkforoecdstatisticalactivi-ties.htm (accessed February 2021).Search in Google Scholar

Reboot. 2017. Understanding the Users of Open Data. Reboot Inc. for NYC Open Data. Available at: https://opendata.cityofnewyork.us/wp-content/uploads/2017/07/Understanding-the-Users-of-Open-Data_Reboot.pdf (accessed February 2021).Search in Google Scholar

Riley, J. 2017. Understanding Metadata: What is Metadata, and What is it For?: A Primer. Baltimore: National Information Standards Organization. Available at: http://www.niso.org/publications/press/UnderstandingMetadata.pdf (accessed February 2021).Search in Google Scholar

Severo, M, A. Feredj, and A. Romele. 2016. “Soft Data and Public Policy: Can Social Media Offer Alternatives to Official Statistics in Urban Policymaking.” Policy and Internet 8, 3: 354–372. DOI: https://doi.org/10.1002/poi3.127.10.1002/poi3.127Search in Google Scholar

Solove, D.J. 2006. “A Taxonomy of Privacy.” University of Pennsylvania Law Review 154. 3: 477–560. Available at: https://scholarship.law.upenn.edu/penn_law_review/-vol154/iss3/1 (accessed February 2021).10.2307/40041279Search in Google Scholar

Struijs, P., B. Braaksma, and P.J.H. Daas. 2014. “Official statistics and Big Data.” Big Data and Society 1, 1: 1–6. DOI: https://doi.org/10.1177/2053951714538417.10.1177/2053951714538417Search in Google Scholar

Townsend, A. 2013. Smart Cities: Big data, Civic Hackers, and the Quest for a New Utopia. New York: W.W. Norton & Co.Search in Google Scholar

UN Big Data Working Group. 2017. Bogota Declaration. United Nations 4th International Conference on Big Data for Official Statistics. 8–10 November 2017, Bogotá, Colombia. Available at: https://unstats.un.org/unsd/bigdata/conferences/2017/Bogota%20declaration%20-%20Final%20version.pdf (accessed February 2021).Search in Google Scholar

UNECE. 1992. Fundamental Principles of Official Statistics. United Nations Economic Commission for Europe. Available at: https://unece.org/statistics/fundamental-principles-official-statistics (accessed February 2021).Search in Google Scholar

UNECE. 2014. A Suggested Framework for the Quality of Big Data. United Nations Economic Commission for Europe. Available at: https://statswiki.unece.org/download/attachments/108102944/Big%20Data%20Quality%20Framework%20-%20final-%20Jan08-2015.pdf (accessed February 2021).Search in Google Scholar

White, J.M. 2019. “Standardising the city: A material-discursive genealogy of CPA-I_001, ISO 37120 and BSI PAS 181.” Doctoral thesis, Maynooth University. Available at: http://mural.maynoothuniversity.ie/10848/ (accessed February 2021).Search in Google Scholar

WHO. 2006. WHO Air quality guidelines Global update 2005: particulate matter, ozone, nitrogen dioxide and sulfur dioxide. World Health Organization Regional Office for Europe. Copenhagen. Available at: https://apps.who.int/iris/handle/10665/107823 (accessed February 2021).Search in Google Scholar

Zein, A. 2020. “Short-term effects of the coronoavirus outbreak: what does the shipping data say?” UNCTAD Transport and Trade Facilitation Newsletter N885 – First Quarter 2020. 48.Search in Google Scholar