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TYDR - Track Your Daily Routine. Android App for Tracking Smartphone Sensor and Usage Data


Beierle, Felix; Tran, Vinh Thuy; Allemand, Mathias; Neff, Patrick; Schlee, Winfried; Probst, Thomas; Pryss, Rüdiger; Zimmermann, Johannes (2018). TYDR - Track Your Daily Routine. Android App for Tracking Smartphone Sensor and Usage Data. In: MobileSoft 2018: 5th IEEE/ACM International Conference on Mobile Software Engineering and Systems, Gothenburg, Sweden, 27 May 2018 - 28 May 2018, 1-4.

Abstract

We present the Android app TYDR (Track Your Daily Routine) which tracks smartphone sensor and usage data and utilizes standardized psychometric personality questionnaires. With the app, we aim at collecting data for researching correlations between the tracked smartphone data and the user's personality in order to predict personality from smartphone data. In this paper, we highlight our approaches in addressing the challenges in developing such an app. We optimize the tracking of sensor data by assessing the trade-off of size of data and battery consumption and granularity of the stored information. Our user interface is designed to incentivize users to install the app and fill out questionnaires. TYDR processes and visualizes the tracked sensor and usage data as well as the results of the personality questionnaires. When developing an app that will be used in psychological studies, requirements posed by ethics commissions / institutional review boards and data protection officials have to be met. We detail our approaches concerning those requirements regarding the anonymized storing of user data, informing the users about the data collection, and enabling an opt-out option. We present our process for anonymized data storing while still being able to identify individual users who successfully completed a psychological study with the app.

Abstract

We present the Android app TYDR (Track Your Daily Routine) which tracks smartphone sensor and usage data and utilizes standardized psychometric personality questionnaires. With the app, we aim at collecting data for researching correlations between the tracked smartphone data and the user's personality in order to predict personality from smartphone data. In this paper, we highlight our approaches in addressing the challenges in developing such an app. We optimize the tracking of sensor data by assessing the trade-off of size of data and battery consumption and granularity of the stored information. Our user interface is designed to incentivize users to install the app and fill out questionnaires. TYDR processes and visualizes the tracked sensor and usage data as well as the results of the personality questionnaires. When developing an app that will be used in psychological studies, requirements posed by ethics commissions / institutional review boards and data protection officials have to be met. We detail our approaches concerning those requirements regarding the anonymized storing of user data, informing the users about the data collection, and enabling an opt-out option. We present our process for anonymized data storing while still being able to identify individual users who successfully completed a psychological study with the app.

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Additional indexing

Item Type:Conference or Workshop Item (Paper), not_refereed, original work
Communities & Collections:06 Faculty of Arts > Institute of Psychology
Dewey Decimal Classification:150 Psychology
Language:English
Event End Date:28 May 2018
Deposited On:20 Nov 2018 10:59
Last Modified:24 Sep 2019 23:53
OA Status:Green
Free access at:Official URL. An embargo period may apply.
Publisher DOI:https://doi.org/10.1145/3197231.3197235
Official URL:https://arxiv.org/abs/1803.06720
Project Information:

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