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This article explains what time time dimensions are, why they matter for health research and business data analysis, and how they solve the common but frustrating problem of analyzing time-series data that sits at variable time scales. Ready-to-use code AI assistant prompts to generate these tables is freely available in the EFDC AI Prompt Database on GitHub, with support for multiple platforms including Power BI / Power Query (M), Python, R, SQL, JavaScript, Lua, PowerShell, and Bash.

A compilation of software tools used by MDEN mobile tech researchers for working with mobile data, including: wearable programming, mobile app development, data extraction, data analysis, data presentation and visualizations, and data pipelines.

This article is a listing of data dictionaries and data models for datasets that utilize mobile data (wearables, mobile apps, surveys, smartwatch apps, phone sensors, and more).

The Mobile Data Expert Network (MDEN) is a collaborative problem-solving network at the University of Michigan comprised of staff and junior faculty who develop and share tools and documentation that enhance the reproducibility and rigor of U-M studies using mobile devices. MDEN members routinely host presentations about mobile data and tools. These are the recordings available from the 2025-2026 academic year.

Continuous glucose monitors (CGMs) provide important metrics about the health of study participants. They can provide a time-series of estimated glucose values, and metrics around hypoglycemia episodes (low blood sugar). However, CGMs may falsely read low glucose values and issue "low glucose" alerts when they are being depressed, commonly known as "compression lows." This articles explores some of the common causes and solutions.

This article provides general guidance for sharing mobile data, based on the lessons learned by members of MeTRIC (https://metric.umich.edu), and evolving best practices from government and academic institutions worldwide.

DIGIT-MI recordings from the 2022-2023 academic year. DIGIT-MI monthly meetings allow investigators across the University of Michigan to connect, learn, and share resources that encourage the increased use of digital and mobile technologies and mental wellness in research across multiple disciplines.