IDEAS home Printed from https://ideas.repec.org/a/eee/jotrge/v92y2021ics0966692321000739.html
   My bibliography  Save this article

The impact of privacy protection measures on the utility of crowdsourced cycling data

Author

Listed:
  • Raturi, Varun
  • Hong, Jinhyun
  • McArthur, David Philip
  • Livingston, Mark

Abstract

The use of new forms of data in the transport research domain is rapidly gaining popularity. However, these data come with specific challenges and one of the major concerns is maintaining the privacy of data subjects. One widely used approach to anonymise the data is to apply binning. Recently, data from activity-tracking applications like Strava has been utilised to study and analyse active travel. Due to privacy concerns, Strava has started providing data in a discretised format from July 2018. In this study, we aim to analyse the impact of the binning criteria on the utility of the crowdsourced data by using Strava data from 2013 to 2016 for the city of Glasgow. We applied the Strava binning criteria on the original dataset at three different temporal aggregations (i.e., Hourly, Daily and Monthly) and conducted different analyses to examine its impacts. First, we compared manual cycling counts with original and binned cycling counts from Strava data. Second, net-errors were calculated by comparing original and binned cycling counts from Strava data. Third, we estimated spatial autocorrelation statistics based on original and binned Strava counts and investigated the extent to which research outcomes change because of the binning approach. Our results confirmed significant amount of information loss. Worryingly, we also show that conclusions reached by previous studies could have been reversed if the new specification of the data had been used. We outline here what precautions researchers and planners should take when working with the binned data.

Suggested Citation

  • Raturi, Varun & Hong, Jinhyun & McArthur, David Philip & Livingston, Mark, 2021. "The impact of privacy protection measures on the utility of crowdsourced cycling data," Journal of Transport Geography, Elsevier, vol. 92(C).
    • Handle: RePEc:eee:jotrge:v:92:y:2021:i:c:s0966692321000739
    DOI: 10.1016/j.jtrangeo.2021.103020
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0966692321000739
    Download Restriction: no
    File URL: https://libkey.io/10.1016/j.jtrangeo.2021.103020?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. Jinhyun Hong & David Philip McArthur & Mark Livingston, 2020. "The evaluation of large cycling infrastructure investments in Glasgow using crowdsourced cycle data," Transportation, Springer, vol. 47(6), pages 2859-2872, December.
    2. Jaimee Lederman & Brian D. Taylor & Mark Garrett, 2016. "A private matter: the implications of privacy regulations for intelligent transportation systems," Transportation Planning and Technology, Taylor & Francis Journals, vol. 39(2), pages 115-135, March.
    3. Griffin, Greg Phillip & Jiao, Junfeng, 2015. "Where does bicycling for health happen? Analysing volunteered geographic information through place and plexus," SocArXiv 5gy3u, Center for Open Science.
    4. Mark Padgham, 2012. "Human Movement Is Both Diffusive and Directed," PLOS ONE, Public Library of Science, vol. 7(5), pages 1-11, May.
    5. Daniel Nunan & Marialaura Di Domenico, 2017. "Big Data: A Normal Accident Waiting to Happen?," Journal of Business Ethics, Springer, vol. 145(3), pages 481-491, October.
    6. Gustavo Romanillos & Martin Zaltz Austwick & Dick Ettema & Joost De Kruijf, 2016. "Big Data and Cycling," Transport Reviews, Taylor & Francis Journals, vol. 36(1), pages 114-133, January.
    7. McArthur, David Philip & Hong, Jinhyun, 2019. "Visualising where commuting cyclists travel using crowdsourced data," Journal of Transport Geography, Elsevier, vol. 74(C), pages 233-241.
    8. Jestico, Ben & Nelson, Trisalyn & Winters, Meghan, 2016. "Mapping ridership using crowdsourced cycling data," Journal of Transport Geography, Elsevier, vol. 52(C), pages 90-97.
    9. Cavill, Nick & Kahlmeier, Sonja & Rutter, Harry & Racioppi, Francesca & Oja, Pekka, 2008. "Economic analyses of transport infrastructure and policies including health effects related to cycling and walking: A systematic review," Transport Policy, Elsevier, vol. 15(5), pages 291-304, September.
    10. Hochmair, Hartwig H. & Bardin, Eric & Ahmouda, Ahmed, 2019. "Estimating bicycle trip volume for Miami-Dade county from Strava tracking data," Journal of Transport Geography, Elsevier, vol. 75(C), pages 58-69.
    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. Mohammad Anwar Alattar & Caitlin Cottrill & Mark Beecroft, 2021. "Sources and Applications of Emerging Active Travel Data: A Review of the Literature," Sustainability, MDPI, vol. 13(13), pages 1-17, June.

    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. Md Mintu Miah & Kate Kyung Hyun & Stephen P. Mattingly & Hannan Khan, 2023. "Estimation of daily bicycle traffic using machine and deep learning techniques," Transportation, Springer, vol. 50(5), pages 1631-1684, October.
    2. Hong, Jinhyun & Philip McArthur, David & Stewart, Joanna L., 2020. "Can providing safe cycling infrastructure encourage people to cycle more when it rains? The use of crowdsourced cycling data (Strava)," Transportation Research Part A: Policy and Practice, Elsevier, vol. 133(C), pages 109-121.
    3. Ali Al-Ramini & Mohammad A Takallou & Daniel P Piatkowski & Fadi Alsaleem, 2022. "Quantifying changes in bicycle volumes using crowdsourced data," Environment and Planning B, , vol. 49(6), pages 1612-1630, July.
    4. McArthur, David Philip & Hong, Jinhyun, 2019. "Visualising where commuting cyclists travel using crowdsourced data," Journal of Transport Geography, Elsevier, vol. 74(C), pages 233-241.
    5. Munira, Sirajum & Sener, Ipek N., 2020. "A geographically weighted regression model to examine the spatial variation of the socioeconomic and land-use factors associated with Strava bike activity in Austin, Texas," Journal of Transport Geography, Elsevier, vol. 88(C).
    6. Jinhyun Hong & David Philip McArthur & Mark Livingston, 2020. "The evaluation of large cycling infrastructure investments in Glasgow using crowdsourced cycle data," Transportation, Springer, vol. 47(6), pages 2859-2872, December.
    7. Stella R. Harden & Nadine Schuurman & Peter Keller & Scott A. Lear, 2022. "Neighborhood Characteristics Associated with Running in Metro Vancouver: A Preliminary Analysis," IJERPH, MDPI, vol. 19(21), pages 1-13, November.
    8. Hochmair, Hartwig H. & Bardin, Eric & Ahmouda, Ahmed, 2019. "Estimating bicycle trip volume for Miami-Dade county from Strava tracking data," Journal of Transport Geography, Elsevier, vol. 75(C), pages 58-69.
    9. Tineke de Jong & Lars Böcker & Christian Weber, 2023. "Road infrastructures, spatial surroundings, and the demand and route choices for cycling: Evidence from a GPS-based mode detection study from Oslo, Norway," Environment and Planning B, , vol. 50(8), pages 2133-2150, October.
    10. Jill Walker Rettberg, 2020. "Situated data analysis: a new method for analysing encoded power relationships in social media platforms and apps," Palgrave Communications, Palgrave Macmillan, vol. 7(1), pages 1-13, December.
    11. Mark Livingston & David McArthur & Jinhyun Hong & Kirstie English, 2021. "Predicting cycling volumes using crowdsourced activity data," Environment and Planning B, , vol. 48(5), pages 1228-1244, June.
    12. Alattar, Mohammad Anwar & Cottrill, Caitlin & Beecroft, Mark, 2021. "Public participation geographic information system (PPGIS) as a method for active travel data acquisition," Journal of Transport Geography, Elsevier, vol. 96(C).
    13. Mário Meireles & Paulo J. G. Ribeiro, 2020. "Digital Platform/Mobile App to Boost Cycling for the Promotion of Sustainable Mobility in Mid-Sized Starter Cycling Cities," Sustainability, MDPI, vol. 12(5), pages 1-27, March.
    14. Nina Cesare & Pallavi Dwivedi & Quynh C. Nguyen & Elaine O. Nsoesie, 2019. "Use of social media, search queries, and demographic data to assess obesity prevalence in the United States," Palgrave Communications, Palgrave Macmillan, vol. 5(1), pages 1-9, December.
    15. Havinga, Ilan & Bogaart, Patrick W. & Hein, Lars & Tuia, Devis, 2020. "Defining and spatially modelling cultural ecosystem services using crowdsourced data," Ecosystem Services, Elsevier, vol. 43(C).
    16. Kyuhyun Lee & Ipek N. Sener, 2019. "Understanding Potential Exposure of Bicyclists on Roadways to Traffic-Related Air Pollution: Findings from El Paso, Texas, Using Strava Metro Data," IJERPH, MDPI, vol. 16(3), pages 1-20, January.
    17. Xie, Xiao-Feng & Wang, Zunjing Jenipher, 2018. "Examining travel patterns and characteristics in a bikesharing network and implications for data-driven decision supports: Case study in the Washington DC area," Journal of Transport Geography, Elsevier, vol. 71(C), pages 84-102.
    18. Jasmina Ćetković & Slobodan Lakić & Angelina Živković & Miloš Žarković & Radoje Vujadinović, 2021. "Economic Analysis of Measures for GHG Emission Reduction," Sustainability, MDPI, vol. 13(4), pages 1-25, February.
    19. Radzimski, Adam & Dzięcielski, Michał, 2021. "Exploring the relationship between bike-sharing and public transport in Poznań, Poland," Transportation Research Part A: Policy and Practice, Elsevier, vol. 145(C), pages 189-202.
    20. Hu, Yujie & Zhang, Yongping & Lamb, David & Zhang, Mingming & Jia, Peng, 2019. "Examining and optimizing the BCycle bike-sharing system – A pilot study in Colorado, US," Applied Energy, Elsevier, vol. 247(C), pages 1-12.

    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:eee:jotrge:v:92:y:2021:i:c:s0966692321000739. 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/journal-of-transport-geography .

    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.