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

arXiv: https://arxiv.org/abs/2604.11944 · HTML: https://mlsanity.com/paper/2604.11944/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 15 references that are in the map.
- First posted on arXiv 13 Apr 2026.

## Builds on (most cited first, 1 of 1)

- [MetaboNet: The Largest Publicly Available Consolidated Dataset for Type 1 Diabetes Management](https://mlsanity.com/paper/2601.11505/) (2026)

## Abstract (arXiv)

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