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Improving Time Use Measurement with Personal Big Data Collection – The Experience of the European Big Data Hackathon 2019

Author

Listed:
  • Zeni Mattia
  • Bison Ivano
  • Giunchiglia Fausto

    (University of Trento, via Calepina, 14 – 38122Trento, Italy.)

  • Reis Fernando
  • Gauckler Britta

    (European Commission – DG EUROSTAT, 5 rue Alphonse Weicker, Luxembourg.)

Abstract

This article assesses the experience with i-Log at the European Big Data Hackathon 2019, a satellite event of the New Techniques and Technologies for Statistics (NTTS) conference, organised by Eurostat. i-Log is a system that enables capturing personal big data from smartphones’ internal sensors to be used for time use measurement. It allows the collection of heterogeneous types of data, enabling new possibilities for sociological urban field studies. Sensor data such as those related to the location or the movements of the user can be used to investigate and gain insights into the time diaries’ answers and assess their overall quality. The key idea is that the users’ answers are used to train machine-learning algorithms, allowing the system to learn from the user’s habits and to generate new time diaries’ answers. In turn, these new labels can be used to assess the quality of existing ones, or to fill the gaps when the user does not provide an answer. The aim of this paper is to introduce the pilot study, the i-Log system and the methodological evidence that emerged during the survey.

Suggested Citation

  • Zeni Mattia & Bison Ivano & Giunchiglia Fausto & Reis Fernando & Gauckler Britta, 2021. "Improving Time Use Measurement with Personal Big Data Collection – The Experience of the European Big Data Hackathon 2019," Journal of Official Statistics, Sciendo, vol. 37(2), pages 341-365, June.
    • Handle: RePEc:vrs:offsta:v:37:y:2021:i:2:p:341-365:n:5
    DOI: 10.2478/jos-2021-0015
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    References listed on IDEAS

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    1. Stella Chatzitheochari & Kimberly Fisher & Emily Gilbert & Lisa Calderwood & Tom Huskinson & Andrew Cleary & Jonathan Gershuny, 2018. "Using New Technologies for Time Diary Data Collection: Instrument Design and Data Quality Findings from a Mixed-Mode Pilot Survey," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 137(1), pages 379-390, May.
    2. Merz, Joachim, 2009. "Time Use and Time Budgets – Improvements, Future Challenges and Recommendations," MPRA Paper 16304, University Library of Munich, Germany.
    3. Juster, F Thomas & Stafford, Frank P, 1991. "The Allocation of Time: Empirical Findings, Behavioral Models, and Problems of Measurement," Journal of Economic Literature, American Economic Association, vol. 29(2), pages 471-522, June.
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