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Dr. Sarah Sperry and Victoria Murphy of the Emotion and Temporal Dynamics (EmoTe) Lab at the University of Michigan created EMA-CleanR, an R-based program for efficient pre-processing, cleaning, and visualization of Ecological Momentary Assessment (EMA) survey data. This article documents how to use EMA-CleanR and how it works.

Flatten It uses iteration (no recursion) to flatten iterables into a dictionary where each key is a reference path and each value is the value at the respective path.  This simple flattening algorithm has been used for diffing deeply nested JSON structures and for transforming hierarchical data into a tabular data model.

TrackMaster uses Power Automate for several automated tasks, from keeping the People list up-to-date with data from MCommunity, to getting info from Office 365, to bulk uploads and more. These automations are called "flows" in Power Automate. This article provides a snapshot of all the Power Automate flows that are used by TrackMaster as of the latest version.
All code is available in GitHub at: https://github.com/DepressionCenter/TrackMaster

Overview of the Sleep Data Automation code, a project developed by the Mobile Technologies Core and the Sleep & Circadian Rhythm Laboratory to automate the process of cleaning sleep data from Fitbit fitness trackers and comparing or joining it to self-reported sleep diary data.