Mobile Phones in Data Collection

Abstract

Mobile phones are increasingly popular tools not only for daily use but also for research purposes. The authors systematically searched related literature using mobile phones as a tool for data collection and found 171 publications consisting of review, empirical, methodological, and theoretical studies in various disciplines such as medicine, engineering, and education. After reviewing contributions of previous review studies, the authors presented a description of data collection process consisting of four steps and used these four steps as a framework to review the existing empirical literature. The authors then reviewed contributions of methodological and theoretical studies, and end with a summary of current practices of collecting mobile data. Current challenges and future directions were also mentioned.

The Going Out In Sydney App: Evaluating the Utility of a Smartphone App for Monitoring Real-World Illicit Drug Use and Police Encounters Among Festival and Club Goers

“…Our experience using the GOIS app adds to the existing research showing the utility of apps for research data collection on topics as diverse as medicine, engineering, education, time usage studies, and alcohol consumption, 22,23,29 suggesting that smartphone apps can also be useful for research data collection on illicit drug use and drugs policing. Given the challenges in getting access to data on such topics, this is welcome news.…”

“…Overall, such experiences suggest that apps can offer benefits for research data collection. [21][22][23][24]29 Two key challenges in the use of smartphone apps are technical hitches/problems in poor design and privacy: namely that the use of mobile technology makes it harder to control where and how collected data are shared. 21,29,31 That said, increasing studies have showed that piloting and anonymisation can lessen both issues.…”

“…[21][22][23][24]29 Two key challenges in the use of smartphone apps are technical hitches/problems in poor design and privacy: namely that the use of mobile technology makes it harder to control where and how collected data are shared. 21,29,31 That said, increasing studies have showed that piloting and anonymisation can lessen both issues. For example, Şahin and Yan 29 found that 29 of 115 studies using mobile phones collected anonymous data and 18 collected pseudoanonymous data (where participants were given a nickname).…”

“…real-time or close-to-real-time that can better capture the context of the behaviour of interest. 22,23,29,35 More specifically, the GOIS app brings to the fore 3 benefits for drug policy research. First, it has showed that the apps can be used to capture data not only on behaviour (illicit drug use) but also on policy responses to that behaviour (policing).…”

Towards Recognising Individual Behaviours from Pervasive Mobile Datasets in Urban Spaces

“…There are many works that have considered behavior recognition in ubiquitous computing and their relevant subsets, which focus primarily on pervasive datasets stored in BTSs as a subject of these research interests. Mobile phone datasets have gained both in importance and popularity (see the review paper byŞahin and Zhen [1]), both for empirical and theoretical research purposes concerning medicine [2,3], engineering, education, and even ethnic segregation [4]. The CDR datasets are the subject of intensive pre-handling and cleaning to obtain big dataset for further studies that are concerned with behaviors and activities [5].…”