POSE: Phase I: Creating an Open-Source Ecosystem / Governance for the mindLAMP Platform

Award ID: 2449435

This Pathways to Enable Open-Source Ecosystems (POSE) project improves how researchers and clinicians use everyday technology, like smartphones, to better understand health in real-world settings. Most people carry smartphones that can collect useful information such as steps taken, sleep patterns, and phone use. This information can offer insight into a persons well-being and has already helped researchers detect early signs of mental health problems, track recovery from surgery, and study cognitive decline. The team developed mindLAMP, the leading open-source platform for collecting health data. As more people use this technology, there is a growing need for shared guidance, support, and coordination. This project builds the foundation for a community-driven open-source ecosystem. Through interviews, surveys, and workshops, the team will identify user needs, bring developers and researchers together, and explore how to structure a sustainable and involved community. The results of this planning phase guide the future development of a shared framework, called LAMPOST, that helps more people use smartphone-based data to advance science and improve health. The primary beneficiaries will be researchers, healthcare providers, and in time, any patient whose health condition could be better understood through real-world digital data. This Pathways to Enable Open-Source Ecosystems (POSE) project addresses a core challenge in digital phenotyping research. While mindLAMP, an open-source smartphone-based platform, is already widely used in over 50 clinical and research settings, its growing user base remains siloed. Research teams, software developers, and clinicians often work independently, collecting data, developing features, and applying the platform in ways that are not coordinated or shared. As a result, knowledge about best practices, technical approaches, and real-world impact is fragmented, limiting the fields ability to reproduce findings and advance medical research. The goal of this project is to lay the foundation for a sustainable open-source ecosystem that unites all contributors. The team will define core software assets, identify governance needs, and explore models for long-term maintenance and community participation. Through structured interviews and stakeholder workshops, the team will map the current use of mindLAMP, identify barriers to collaboration, and design processes to improve transparency and interoperability. Given the platforms use in clinical settings and its handling of health-related data, the project will also engage legal experts to develop models for responsible data sharing and compliance with privacy regulations. The anticipated outcome is a shared ecosystem roadmap and a community framework that supports future scaling, sustainability, and scientific progress. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Program Director: Florence Rabanal