Information for Researchers
Are you planning a research project that involves collecting digital behavioral data?
The Digital Device Use Self-Monitoring Platform (D2USP) is a research infrastructure that advances our shared understanding of how digital devices are used and how such use affects society, individual well-being, and productivity. D2USP supports both researchers and citizens by providing PersonalAnalytics, a privacy-friendly, customizable, and easy-to-use software for the automated collection and anonymized analysis of digital behavioral data, which can be used for both personal and scientific purposes.
Instead of building the data-collection infrastructure for a field study from scratch, you can fork PersonalAnalytics, configure it for your study, and deploy it to your participants. Code signing, automatic updates, and a privacy-friendly data export are already built in. The software has been used across more than a dozen peer-reviewed field studies at venues such as CHI, CSCW, DIS, and TSE, with over a thousand participants.
Example applications
To make it concrete, here are a few study designs that PersonalAnalytics is well suited for. Some mirror projects already running on the platform; others are open directions we consider worth pursuing.
Example 1: Computer use in (higher) education
Combines surveys, experience sampling, and digital usage data to understand how students actually work, study, and get distracted. (Target group: students.)
Example 2: User interaction with specific digital content
Studies the real-world effects of social-media and news consumption in the field, using computer-usage data, short experience-sampling surveys, and complementary interviews. (Target group: citizens.)
Example 3: Digitalized work regimes, digital hygiene, and self-management
Remote and hybrid work models bring new challenges for knowledge workers. A project could investigate how digital usage data helps to detect and reduce negative health effects (such as overwork or fragmentation) early, and support users in self-management and reflection. (Target group: knowledge workers.)
Example 4: How people work with AI assistants
Captures when and how participants reach for chatbots and AI tools (e.g. coding assistants) in their everyday work, and combines this with self-reports on trust, perceived usefulness, and cognitive effort, to study how AI is actually integrated into work rather than just how people describe their use. (Target group: knowledge workers, students.)
Example 5: Effects of AI use on focus and skills
Combines interaction data with experience sampling to pursue questions such as: does heavy use of AI assistants go together with more fragmented attention, does it change help-seeking behavior or how long people stay on a task? (Target group: knowledge workers, students.)
For an overview of projects already using D2USP successfully, see current and past studies.
How to start
We recommend first looking at some of the past studies that have used PersonalAnalytics successfully.
On GitHub we manage the open-source code, collect bug reports, plan upcoming releases, and document the software. The page PersonalAnalytics for Researchers describes step by step how to configure the software for your own research project, including configuration parameters, code signing, and deployment. For an overview of what the software can do, see PersonalAnalytics Software.
For questions, please contact Dr. André Meyer or Dr. Malte Doehne.
The D2USP platform is co-funded by the Digital Society Initiative (DSI) of the University of Zurich (UZH). The project team is keen to connect with researchers from the DSI, UZH, and other institutions who would like to use the infrastructure for their own research projects.