Building a Data Management Platform for Longitudinal Athlete Health Monitoring
Help design a data platform to manage complex, multi-source data from a sports science study. Includes biological samples, wearables, exercise tests, and questionnaires. Ideal for students in programming, data science, or IT.
This project offers an opportunity to contribute to a real-world sports science research study by developing a data management platform that can handle longitudinal data from multiple sources. The study involves weekly, monthly, and six-monthly measurements, including biological samples (analyzed in batches), wearable device outputs, point-of-care test results, exercise test data, and questionnaire responses.
Your task will be to work on designing a system, preferably in Python or R, that can structure, store, and link these diverse data types, including metadata from sample collection and testing protocols. The platform should support future analysis and visualization, and ideally include basic user interface elements for data entry and review. The platform/code, but not the data, can be open source.
No prior domain knowledge in sports science is required, but interest in applied data workflows and good programming skills are essential. The student will be supervised by a researcher in sports science and can be supported by an internal IT supervisor for technical guidance.
Sustainability goals
Project information
Project duration
260101-270630
Project institutions
Project lead
Sounds interesting?
In that case you're more than welcome to submit your interest in participating in the project!
Tell us which programme and which year you are studying. Motivate your participation and describe why you are interested in the project. Also include your cellphone number such that we can easily reach you. Your information will not be stored.