A Survey on Mobile Data Uses

A Survey on Mobile Data Uses

Christian Colot (Department of Business Administration, University of Namur, Namur, Belgium), Isabelle Linden (Department of Business Administration, FOCUS Research Group, University of Namur, Namur, Belgium) and Philippe Baecke (Vlerick Business School, Gent, Belgium)
Copyright: © 2016 |Pages: 21
DOI: 10.4018/IJDSST.2016040103
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Mobile devices leave an unprecedented volume and variety of digital traces of human beings. In this paper, the authors propose an overview of multiple uses of mobile data published in the scientific literature. The organization of the survey follows a typology built on two criteria: interaction level and focus of analysis. Crossing these two dimensions would suggest 8 research areas. Only 4 of them are actually covered by the collected pieces of work. They are discussed in turn showing off the main characteristics of them. Finally, the discussion of the 4 remaining areas highlights new research areas with a special focus on the possibility to use mobile data to influence individual users towards efficient collective behaviors. To conclude, current and future research avenues suggest that mobile devices and their underlying data are likely to be employed in many domains and may be used not only to observe human life but also to influence it.
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2. Context

This study focuses on the use of mobile data and is part of a research project towards a better insight on mobile research. In particular, a previous work (Colot et al., 2015) addresses data point of view of mobile: different kinds of information are identified based on mobile data and are organized in a framework called Mobile 3D (M3D) model. This typology is later referred in this article as support for the investigation of the different research areas. Figure 1 gives an overview of the M3D model. The M3D model classifies mobile information according to three dimensions: context, time and source. Each cell represents a specific set of information classified according to the three axes.On the context axis, five categories are considered:

Figure 1.

Mobile 3D model: the dimensions

  • • personal situation of the user: it covers any specific information obtained with mobile data about him from inside: medical parameters (e.g.: blood pressure, body temperature), state of mind, feelings, etc.;

  • • environmental situation of the user: it includes the localization of the user and some more information derived from his/her localization like the corresponding weather or the kind of land;

  • • interaction between humans (proximity based or not);

  • • interaction between human-machine: it refers to interaction of the user with his mobile device);

  • • interaction between machines: it includes interaction between the mobile device and another device.

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