Stanford Screenomics
Stanford Screenomics
A powerful platform providing frameworks, tools, and infrastructure to capture and analyze smartphone-based digital trace data.
We are redefining how human behavior, attention, and well-being are studied in the digital age. Smartphones are ubiquitous, with individuals of all ages all over the world using them to do a wider variety of tasks. The merging of digital life into daily life opens new opportunities to study an increasingly wide array of human behaviors. By capturing real-time data from personal devices, the Screenomics platform provides a direct, dynamic view into how people think, feel, act, and interact as they go about their daily lives. Our platform empowers open, human-centered research that advances knowledge of and our ability to improve the human experience.
Screenomics is an open-source, privacy-aware platform for collecting high-resolution digital life data from study participants’ Android smartphones. The platform captures moment-by-moment screenshots alongside complementary signals such as location, physical activity, screentime, and user-device interactions. These data are transformed into structured, research-ready traces that enable researchers to unobtrusively observe real-world behavior as it naturally unfolds across apps, platforms, and daily contexts, without relying on self-reports or artificial lab settings.
Screenomics is designed to advance open, transparent, and reproducible research. The platform is modular, easily customizable (even without coding experience), and extensible. The flexible design supports a wide range of study designs across disciplines. We foster collaboration through shared infrastructure, community-driven development, and open tools that accelerate discovery in behavioral and psychological science, mental and physical health, education, and digital media. Ethical data collection and strong privacy protections are central to the Screenomics approach.
From digital health to media studies, Screenomics flexibly adapts to diverse research goals. We provide researcher/developer-friendly, customizable processing pipelines and comprehensive documentation to support studies of all scales and complexities. We also partner directly with researchers to develop new features, support integration, and share best practices.
Our approach enables science that reflects the real diversity of people’s lives—across geographies, cultures, languages, and digital habits. By passively capturing screen and device data in situ, Screenomics expands opportunity for researchers to obtain ecologically valid, individual- and population-representative, and socially impactful data that informs knowledge and improvement of human experience.
Have a question or want to contribute? Visit our Discussion Forum to submit inquiries, propose features, report bugs, or share modules.
Stanford University
450 Jane Stanford Way
Stanford, CA 94305