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Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - Collecting shared experiences through lifelogging
T2 - lessons learned
AU - Clinch, Sarah
AU - Davies, Nigel Andrew Justin
AU - Mikusz, Mateusz
AU - Metzger, Paul
AU - Langheinrich, Marc
AU - Schmidt, Albrecht
AU - Ward, Geoff
N1 - ©2015 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
PY - 2016/1
Y1 - 2016/1
N2 - The emergence of widespread pervasive sensing, personal recording technologies, and systems for the quantified self are creating an environment in which one can capture fine-grained activity traces. Such traces have wide applicability in domains such as human memory augmentation, behavior change, and healthcare. However, obtaining these traces for research is nontrivial, especially those containing photographs of everyday activities. To source data for their own work, the authors created an experimental setup in which they collected detailed traces of a group of researchers over 2.75 days. They share their experiences of this process and present a series of lessons learned for other members of the research community conducting similar studies.
AB - The emergence of widespread pervasive sensing, personal recording technologies, and systems for the quantified self are creating an environment in which one can capture fine-grained activity traces. Such traces have wide applicability in domains such as human memory augmentation, behavior change, and healthcare. However, obtaining these traces for research is nontrivial, especially those containing photographs of everyday activities. To source data for their own work, the authors created an experimental setup in which they collected detailed traces of a group of researchers over 2.75 days. They share their experiences of this process and present a series of lessons learned for other members of the research community conducting similar studies.
KW - pervasive computing
KW - big data
KW - data analysis
KW - mobile
KW - pervasive sensing
KW - lifelogging
KW - activity traces
U2 - 10.1109/MPRV.2016.6
DO - 10.1109/MPRV.2016.6
M3 - Journal article
VL - 15
SP - 58
EP - 67
JO - IEEE Pervasive Computing
JF - IEEE Pervasive Computing
SN - 1536-1268
IS - 1
ER -