Abstract

The data collected through smartphone sensors and logs afford researchers a detailed glance into various aspects of people’s everyday life, including information on social interactions, physical activity, mobility, and search for work. To get access to these data, one option is to ask individuals to download a research app to their smartphone, which then passively collects data on the device. In the IAB-SMART study in 2018, we recruited members of the Panel Study Labor Market and Social Security (PASS) to download a research app to their smartphone and share data over a 6-month period (Kreuter et al. 2020). The findings of IAB-SMART highlight both the advantages but also the challenges of the research app approach. While we were able to collect detailed information over a longer period of time from the participants that could then be linked to responses from the PASS survey as well as administrative records, we identified that the approach has limitations in terms of coverage (the IAB-SMART app only worked on Android smartphones), nonparticipation (around 16% of invited PASS members downloaded the app and provided data), and measurement (missing information of what participants did in an app).A recently developed approach for collecting data from smartphones is data donation (Boeschoten et al. 2022), which takes advantage of the EU GDPR’s right of data subjects to receive the data a data controller (e.g., smartphone app or social media platform) holds about them in a structured, commonly used, and machine-readable format and to transfer them to other data controllers (e.g., researchers). The data donation approach has the advantage that no installation of an app is required and that participants only share existing data with the researcher, thus providing a higher degree of control over what data are shared and when. In addition, donated data can include information that is not accessible through a research app, such as interactions that happen in a smartphone app (e.g., interactions on social media or a job search app). However, very little is yet known about how to best implement data donation into existing survey data collection infrastructure and how errors of representation and measurement are affected by the data donation study design.With this project, we will address this gap by implementing data donation in existing survey infrastructure projects at the Institute for Employment Research (IAB). We plan to recruit participants from the PASS panel as well as from the new IAB online probability panel for labour market research (IAB-OPAL) to donate data about their physical activity (daily step count and walking distance from smartphones when available) and their use of and behavior on social media platforms (including general social media platforms such as Facebook, Twitter, and Instagram, but also work-related social media platforms such as LinkedIn; here no smartphone usership is needed). We also plan to investigate the possibilities to request information from accounts that survey participants have on the website of the Federal Employment Agency (BA) and on other job-search platforms. Building on our methodological work on data quality conducted as part of the IAB-SMART study using the rich baseline information available from PASS and IAB-OPAL, we plan to answer research questions about coverage, nonparticipation, and measurement quality of the data donation approach. Our proposed project fits into RA1 of the SPP “Exploration and Integration of Different Data Types”.