English

A unified data format for managing diabetes time-series data: DIAbetes eXchange (DIAX)

Machine Learning 2026-04-15 v1 Quantitative Methods

Abstract

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

Keywords

Cite

@article{arxiv.2604.11944,
  title  = {A unified data format for managing diabetes time-series data: DIAbetes eXchange (DIAX)},
  author = {Elliott C. Pryor and Marc D. Breton and Anas El Fathi},
  journal= {arXiv preprint arXiv:2604.11944},
  year   = {2026}
}

Comments

7 pages, 2 figures