A unified data format for managing diabetes time-series data: DIAbetes eXchange (DIAX)
For researchers and clinicians working with diabetes time-series data, DIAX offers a unified format to simplify data sharing and analysis, but it is an incremental standardization effort rather than a novel algorithmic contribution.
DIAX introduces a standardized JSON-based format for unifying diabetes time-series data (CGM, insulin, meals) to address inconsistent formats across sources. It supports major datasets totaling over 10 million patient-hours and provides conversion tools, promoting interoperability and reproducibility for machine learning applications.
Diabetes devices, including Continuous Glucose Monitoring (CGM), Smart Insulin Pens, and Automated Insulin Delivery systems, generate rich time-series data widely used in research and machine learning. However, inconsistent data formats across sources hinder sharing, integration, and analysis. We present DIAX (DIAbetes eXchange), a standardized JSON-based format for unifying diabetes time-series data, including CGM, insulin, and meal signals. DIAX promotes interoperability, reproducibility, and extensibility, particularly for machine learning applications. An open-source repository provides tools for dataset conversion, cross-format compatibility, visualization, and community contributions. DIAX is a translational resource, not a data host, ensuring flexibility without imposing data-sharing constraints. Currently, DIAX is compatible with other standardization efforts and supports major datasets (DCLP3, DCLP5, IOBP2, PEDAP, T1Dexi, Loop), totaling over 10 million patient-hours of data. https://github.com/Center-for-Diabetes-Technology/DIAX