Exploring informants’ perspectives on the role of crowdsourced active travel data

Mohammad Anwar Alattar* (Corresponding Author), Caitlin Cottrill, Mark Beecroft

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


In the era of ubiquitous technology, crowdsourced data is an emerging frontier for active travel (AT) studies. In this work, we utilize accrued knowledge from interviews and previous literature regarding crowdsourced data strengths, challenges, usefulness and reliability for future informants who seek to embrace crowdsourced data. We review four main types of crowdsourced data: social fitness networks, in-house developed apps, bike sharing systems and participatory mapping. The strengths of crowdsourced data include providing fine data coverage, precision, details, immediacy and empowering users to participate in decision-making. Potential challenges that might arise from adopting this data are related to technical, privacy, proprietorship, financial and data fragmentation factors. In terms of usefulness, crowdsourced data lend themselves to before and after analysis, assessing current infrastructure, and investment prioritization. Reliability issues that may undermine the credibility of crowdsourced data are also discussed, as well as remedies for these concerns.
Original languageEnglish
Pages (from-to)226-250
Number of pages25
JournalTransportation Planning and Technology
Issue number3
Early online date29 Jun 2022
Publication statusPublished - 29 Jun 2022


  • active travel
  • crowdsourced data
  • Social fitness network
  • bike sharing
  • interview


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