IDEAS home Printed from https://ideas.repec.org/a/sae/envirb/v46y2019i9p1756-1768.html
   My bibliography  Save this article

A roundtable discussion: Defining urban data science

Author

Abstract

The field of urban analytics and city science has seen significant growth and development in the past 20 years. The rise of data science, both in industry and academia, has put new pressures on urban research, but has also allowed for new analytical possibilities. Because of the rapid growth and change in the field, terminology in urban analytics can be vague and unclear. This paper, an abridged synthesis of a panel discussion among scholars in Urban Data Science held at the 2019 American Association of Geographers Conference in Washington, D.C., outlines one discussion seeking a better sense of the conceptual, terminological, social, and ethical challenges faced by researchers in this emergent field. The panel outlines the difficulties of defining what is or is not urban data science, finding that good urban data science must have an expansive role in a successful discipline of “city science.†It suggests that “data science†has value as a “signaling†term in industrial or popular science applications, but which may not necessarily be well-understood within purely academic circles. The panel also discusses the normative value of doing urban data science, linking successful practice back to urban life. Overall, this panel report contributes to the wider discussion around urban analytics and city science and about the role of data science in this domain.

Suggested Citation

  • , 2019. "A roundtable discussion: Defining urban data science," Environment and Planning B, , vol. 46(9), pages 1756-1768, November.
    • Handle: RePEc:sae:envirb:v:46:y:2019:i:9:p:1756-1768
    DOI: 10.1177/2399808319882826
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/2399808319882826
    Download Restriction: no
    File URL: https://libkey.io/10.1177/2399808319882826?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. TANNIER, Cécile & THOMAS, Isabelle & VUIDEL, Gilles & FRANKHAUSER, Pierre, 2011. "A fractal approach to identifying urban boundaries," LIDAM Reprints CORE 2297, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Nikhil Naik & Ramesh Raskar & César A. Hidalgo, 2016. "Cities Are Physical Too: Using Computer Vision to Measure the Quality and Impact of Urban Appearance," American Economic Review, American Economic Association, vol. 106(5), pages 128-132, May.
    3. Taylor Shelton & Ate Poorthuis, 2019. "The Nature of Neighborhoods: Using Big Data to Rethink the Geographies of Atlanta’s Neighborhood Planning Unit System," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 109(5), pages 1341-1361, September.
    4. Malcolm J Beynon & Andrew Crawley & Max Munday, 2016. "Measuring and understanding the differences between urban and rural areas," Environment and Planning B, , vol. 43(6), pages 1136-1154, November.
    5. Boeing, Geoff, 2018. "Urban Spatial Order: Street Network Orientation, Configuration, and Entropy," SocArXiv qj3p5, Center for Open Science.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Geoff Boeing & Michael Batty & Shan Jiang & Lisa Schweitzer, 2022. "Urban analytics: History, trajectory and critique," Chapters, in: Sergio J. Rey & Rachel S. Franklin (ed.), Handbook of Spatial Analysis in the Social Sciences, chapter 30, pages 503-516, Edward Elgar Publishing.
    2. Boeing, Geoff, 2020. "Exploring Urban Form Through Openstreetmap Data: A Visual Introduction," SocArXiv rnwgv, Center for Open Science.
    3. Geoff Boeing, 2020. "Urban Street Network Analysis in a Computational Notebook," REGION, European Regional Science Association, vol. 7, pages 39-51.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Edward L. Glaeser & Scott Duke Kominers & Michael Luca & Nikhil Naik, 2018. "Big Data And Big Cities: The Promises And Limitations Of Improved Measures Of Urban Life," Economic Inquiry, Western Economic Association International, vol. 56(1), pages 114-137, January.
    2. Galdo, Virgilio & Li, Yue & Rama, Martin, 2021. "Identifying urban areas by combining human judgment and machine learning: An application to India," Journal of Urban Economics, Elsevier, vol. 125(C).
    3. Andrew Crawley & Max Munday, 2017. "Priority sectors in city regions? Some issues from a study of the Cardiff Capital Region," Local Economy, London South Bank University, vol. 32(6), pages 576-589, September.
    4. Qi Zhou & Lei Guo, 2018. "Empirical approach to threshold determination for the delineation of built-up areas with road network data," PLOS ONE, Public Library of Science, vol. 13(3), pages 1-25, March.
    5. Le Bivic, Camille & Melot, Romain, 2020. "Scheduling urbanization in rural municipalities: Local practices in land-use planning on the fringes of the Paris region," Land Use Policy, Elsevier, vol. 99(C).
    6. Mohamed R Ibrahim & James Haworth & Tao Cheng, 2021. "URBAN-i: From urban scenes to mapping slums, transport modes, and pedestrians in cities using deep learning and computer vision," Environment and Planning B, , vol. 48(1), pages 76-93, January.
    7. Ellen M. Hoffmann & Monish Jose & Nils Nölke & Thomas Möckel, 2017. "Construction and Use of a Simple Index of Urbanisation in the Rural–Urban Interface of Bangalore, India," Sustainability, MDPI, vol. 9(11), pages 1-21, November.
    8. Garrett Dash Nelson, 2021. "Communities, Complexity, and the ‘Conchoration’: Network Analysis and the Ontology of Geographic Units," Tijdschrift voor Economische en Sociale Geografie, Royal Dutch Geographical Society KNAG, vol. 112(4), pages 351-369, September.
    9. Netto, Vinicius M. & Brigatti, Edgardo & Meirelles, João & Ribeiro, Fabiano L. & Pace, Bruno & Cacholas, Caio & Sanches, Patricia Mara, 2018. "Cities, from information to interaction," SocArXiv jgz5d, Center for Open Science.
    10. Imryoung Jeong & Hyunjoo Yang, 2021. "Using maps to predict economic activity," Papers 2112.13850, arXiv.org, revised Apr 2022.
    11. Ka Shing Cheung & Chung Yim Yiu, 2022. "The economics of architectural aesthetics: Identifying price effect of urban ambiences by different house cohorts," Environment and Planning B, , vol. 49(6), pages 1741-1756, July.
    12. Levi J Wolf & Elijah Knaap & Sergio Rey, 2021. "Geosilhouettes: Geographical measures of cluster fit," Environment and Planning B, , vol. 48(3), pages 521-539, March.
    13. Karen Chapple & Ate Poorthuis & Matthew Zook & Eva Phillips, 2022. "Monitoring streets through tweets: Using user-generated geographic information to predict gentrification and displacement," Environment and Planning B, , vol. 49(2), pages 704-721, February.
    14. Ate Poorthuis & Michiel van Meeteren, 2021. "Containment and Connectivity in Dutch Urban Systems: A Network‐Analytical Operationalisation of the Three‐Systems Model," Tijdschrift voor Economische en Sociale Geografie, Royal Dutch Geographical Society KNAG, vol. 112(4), pages 387-403, September.
    15. Peizhen Wang & Ligang Lyu & Jiangang Xu, 2021. "Factors Influencing Rural Households’ Decision-Making Behavior on Residential Relocation: Willingness and Destination," Land, MDPI, vol. 10(12), pages 1-18, November.
    16. Ophélie Merville & Ludivine Launay & Olivier Dejardin & Quentin Rollet & Joséphine Bryère & Élodie Guillaume & Guy Launoy, 2022. "Can an Ecological Index of Deprivation Be Used at the Country Level? The Case of the French Version of the European Deprivation Index (F-EDI)," IJERPH, MDPI, vol. 19(4), pages 1-15, February.
    17. Fleur Visser, 2014. "Rapid mapping of urban development from historic Ordnance Survey maps: An application for pluvial flood risk in Worcester," Journal of Maps, Taylor & Francis Journals, vol. 10(2), pages 276-288, April.
    18. Hiroyuki Usui, 2023. "Cost-Efficient Urban Areas Minimising the Connection Costs of Buildings by Roads: Simultaneous Optimisation of Criteria for Building Interval and Built Cluster Size," Networks and Spatial Economics, Springer, vol. 23(1), pages 65-96, March.
    19. Alessandro Araldi & Giovanni Fusco, 2019. "From the street to the metropolitan region: Pedestrian perspective in urban fabric analysis," Environment and Planning B, , vol. 46(7), pages 1243-1263, September.
    20. Abhishek Nagaraj & Scott Stern, 2020. "The Economics of Maps," Journal of Economic Perspectives, American Economic Association, vol. 34(1), pages 196-221, Winter.

    More about this item

    Keywords

    City analytics; urban data;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:envirb:v:46:y:2019:i:9:p:1756-1768. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.