Exploring informants' perspectives on the role of crowdsourced active travel data. Issue 3 (3rd April 2022)

• Record Type: Journal Article
• Authors: Alattar, Mohammad Anwar; Cottrill, Caitlin; Beecroft, Mark
• Is Part Of: Transportation planning and technology. Volume 45:Issue 3(2022)
• Page Start: 226
• Page End: 250
• Publication Date: 2022-04-03
• Subjects: Active travel -- crowdsourced data -- social fitness networks -- bike-sharing -- interview; Transportation -- Periodicals; Transportation -- Research -- Periodicals; Local transit -- Periodicals; Transportation and state -- Periodicals; 388
• DOI: 10.1080/03081060.2022.2092736
• Languages: English
• ISSNs: 0308-1060

Abstract

ABSTRACT: 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.