Data scientists and biomedical researchers
When preparing a dataset for machine learning model training on Parkinson's gait analysis.
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About
The Dataset mind map template provides a structured breakdown of 95 nodes covering the composition and fields of train, test, unlabeled, and metadata subsets, specifically for Parkinson's disease gait analysis data. This Dataset template organizes key components such as 'AccV' (vertical acceleration), 'StartHesitation', and 'UPDRSIIIOn/UPDRSIIIOff score', making it a practical Dataset cheat sheet for researchers and data scientists. The template visually separates labeled and unlabeled data, annotation information, and metadata files like 'events.csv' and 'daily_metadata.csv', offering a clear overview of data organization and management for biomedical signal processing.
Terms and ConditionsWhen to use this template
Research assistants and data analysts
During data exploration to understand the structure of labeled and unlabeled acceleration data.
Academic researchers and data curators
When documenting dataset schema for a research paper or data repository submission.
How to use this template
Step 1
Launch the Template
Open the .xmind file in Xmind desktop or web application.
Step 2
Explore Data Structure
Navigate through the four main branches (train, test, unlabeled, metadata) to explore the data structure.
Step 3
Customize Dataset Fields
Customize node names and descriptions to match your specific dataset fields.
Step 4
Expand Data Categories
Add new branches or sub-nodes for additional data categories or derived features.
Step 5
Export for Documentation
Export the mind map as an image or PDF for documentation or presentation.
Frequently asked questions
The template covers 95 nodes across train, test, unlabeled, and metadata subsets, detailing fields like acceleration axes (AccV, AccML, AccAP), event indicators, and clinical scores (UPDRS, NFOGQ).
It is structured into four main branches: train (with subfolders tdcsfog/, defog/, notype/), test, unlabeled, and metadata (including .csv files and subject information).
Yes, you can edit node labels, add new branches, or modify field descriptions directly in Xmind to fit your specific dataset or research project.
Yes, it is specifically designed for gait analysis data from Parkinson's patients, including fields like StartHesitation, Turn, Walking, and UPDRS scores.
The template lists events.csv, tasks.csv, daily_metadata.csv, and hidden files like tdcsfog_metadata.csv and defog_metadata.csv for additional test set entries.
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