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A taxonomy for visualisations of personal physical activity data on self-tracking devices and their applications

Research output: Contribution to conference typesPaper

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A taxonomy for visualisations of personal physical activity data on self-tracking devices and their applications. / Alrehiely, Majedah; Eslambolchilar, Parisa; Borgo, Rita.

2018. Paper presented at 32nd International BCS Human Computer Interaction Conference, HCI 2018, Belfast, United Kingdom.

Research output: Contribution to conference typesPaper

Harvard

Alrehiely, M, Eslambolchilar, P & Borgo, R 2018, 'A taxonomy for visualisations of personal physical activity data on self-tracking devices and their applications', Paper presented at 32nd International BCS Human Computer Interaction Conference, HCI 2018, Belfast, United Kingdom, 4/07/2018 - 6/07/2018. https://doi.org/10.14236/ewic/HCI2018.17

APA

Alrehiely, M., Eslambolchilar, P., & Borgo, R. (2018). A taxonomy for visualisations of personal physical activity data on self-tracking devices and their applications. Paper presented at 32nd International BCS Human Computer Interaction Conference, HCI 2018, Belfast, United Kingdom. https://doi.org/10.14236/ewic/HCI2018.17

Vancouver

Alrehiely M, Eslambolchilar P, Borgo R. A taxonomy for visualisations of personal physical activity data on self-tracking devices and their applications. 2018. Paper presented at 32nd International BCS Human Computer Interaction Conference, HCI 2018, Belfast, United Kingdom. https://doi.org/10.14236/ewic/HCI2018.17

Author

Alrehiely, Majedah ; Eslambolchilar, Parisa ; Borgo, Rita. / A taxonomy for visualisations of personal physical activity data on self-tracking devices and their applications. Paper presented at 32nd International BCS Human Computer Interaction Conference, HCI 2018, Belfast, United Kingdom.

Bibtex Download

@conference{498f2fd08d344c6b95133fdf44e09fd0,
title = "A taxonomy for visualisations of personal physical activity data on self-tracking devices and their applications",
abstract = "Self-tracking devices and apps have been widely used for personal data collection, with particular focus on health and physical activity (PA) monitoring. Despite their pervasive use, data representation and data sharing on these devices and apps are still in their infancy. With the aim of contributing towards structuring the design space of personal health visualisation, we present an overview focused on visualisation methods and the typology of tracked data in the most popular health and PA tracking devices and their companion apps/dashboards. Our research method of data collection is based not only on a review of scientific literature in the field, but also on autoethnography, information collected from manufacturers' websites and user manuals as well as online communities and reviews. We then discuss the major issues and limitations users face with regards to health and PA data interpretation and sharing.",
keywords = "Health Tracking, Personal Visualization, Smartphone Apps, Smartwatches Self-tracking, Wearable Devices",
author = "Majedah Alrehiely and Parisa Eslambolchilar and Rita Borgo",
year = "2018",
month = "1",
day = "1",
doi = "10.14236/ewic/HCI2018.17",
language = "English",
note = "32nd International BCS Human Computer Interaction Conference, HCI 2018 ; Conference date: 04-07-2018 Through 06-07-2018",

}

RIS (suitable for import to EndNote) Download

TY - CONF

T1 - A taxonomy for visualisations of personal physical activity data on self-tracking devices and their applications

AU - Alrehiely, Majedah

AU - Eslambolchilar, Parisa

AU - Borgo, Rita

PY - 2018/1/1

Y1 - 2018/1/1

N2 - Self-tracking devices and apps have been widely used for personal data collection, with particular focus on health and physical activity (PA) monitoring. Despite their pervasive use, data representation and data sharing on these devices and apps are still in their infancy. With the aim of contributing towards structuring the design space of personal health visualisation, we present an overview focused on visualisation methods and the typology of tracked data in the most popular health and PA tracking devices and their companion apps/dashboards. Our research method of data collection is based not only on a review of scientific literature in the field, but also on autoethnography, information collected from manufacturers' websites and user manuals as well as online communities and reviews. We then discuss the major issues and limitations users face with regards to health and PA data interpretation and sharing.

AB - Self-tracking devices and apps have been widely used for personal data collection, with particular focus on health and physical activity (PA) monitoring. Despite their pervasive use, data representation and data sharing on these devices and apps are still in their infancy. With the aim of contributing towards structuring the design space of personal health visualisation, we present an overview focused on visualisation methods and the typology of tracked data in the most popular health and PA tracking devices and their companion apps/dashboards. Our research method of data collection is based not only on a review of scientific literature in the field, but also on autoethnography, information collected from manufacturers' websites and user manuals as well as online communities and reviews. We then discuss the major issues and limitations users face with regards to health and PA data interpretation and sharing.

KW - Health Tracking

KW - Personal Visualization

KW - Smartphone Apps

KW - Smartwatches Self-tracking

KW - Wearable Devices

UR - http://www.scopus.com/inward/record.url?scp=85058322576&partnerID=8YFLogxK

U2 - 10.14236/ewic/HCI2018.17

DO - 10.14236/ewic/HCI2018.17

M3 - Paper

AN - SCOPUS:85058322576

ER -

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