On Heterogeneity in Mobile Sensing Applications Aiming at Representative Data Collection

TY - GEN

T1 - On Heterogeneity in Mobile Sensing Applications Aiming at Representative Data Collection

AU - Blunck, Henrik

AU - Bouvin, Niels Olof

AU - Franke, Tobias

AU - Grønbæk, Kaj

AU - Kjærgaard, Mikkel Baun

AU - Lukowicz, Paul

AU - Wüstenberg, Markus

PY - 2013

Y1 - 2013

N2 - Gathering representative data using mobile sensing to answer research questions is becoming increasingly popular, driven by growing ubiquity and sensing capabilities of mobile devices. However, there are pitfalls along this path, which introduce heterogeneity in the gathered data, and which are rooted in the diversity of the involved device platforms, hardware, software versions and participants. Thus, we, as a research community, need to establish good practices and methodologies for addressing this issue in order to help ensure that, e.g., scientific results and policy changes based on collective, mobile sensed data are valid. In this paper, we aim to inform researchers and developers about mobile sensing data heterogeneity and ways to combat it. We do so via distilling a vocabulary of underlying causes, and via describing their effects on mobile sensing---building on experiences from three projects within citizen science, crowd awareness and trajectory tracking.

AB - Gathering representative data using mobile sensing to answer research questions is becoming increasingly popular, driven by growing ubiquity and sensing capabilities of mobile devices. However, there are pitfalls along this path, which introduce heterogeneity in the gathered data, and which are rooted in the diversity of the involved device platforms, hardware, software versions and participants. Thus, we, as a research community, need to establish good practices and methodologies for addressing this issue in order to help ensure that, e.g., scientific results and policy changes based on collective, mobile sensed data are valid. In this paper, we aim to inform researchers and developers about mobile sensing data heterogeneity and ways to combat it. We do so via distilling a vocabulary of underlying causes, and via describing their effects on mobile sensing---building on experiences from three projects within citizen science, crowd awareness and trajectory tracking.

KW - Mobile Sensing

KW - Heterogeneity

KW - Data Collection

KW - Representativeness

U2 - 10.1145/2494091.2499576

DO - 10.1145/2494091.2499576

M3 - Article in proceedings

SN - 978-1-4503-2215-7

SP - 1087

EP - 1098

BT - Proceedings of the 2013 ACM Conference on Pervasive and Ubiquitous Computing Adjunct Publication, UbiComp '13 Adjunct

A2 - Mattern , Friedemann

A2 - Santini , Silvia

PB - Association for Computing Machinery

T2 - ACM Conference on Pervasive and Ubiquitous Computing Adjunct Publication

Y2 - 8 September 2013 through 12 September 2013

ER -