UTX000

UTX000 is a study that gathers from multiple individuals/studies and contains a wealth of moment-by-moment data on a person and their envrionment. The project is an arm of Whole Communities, Whole Health Iniative - a UT Grand Challenge. The goals of this particular project are to:

• reconcile multiple data modalities
• establish connections between variables from the same and disparate data modalities
• provide actionable results for participants

Interested in the nitty-gritty of the project? Check out more on the Wiki page.

Data Modalities

The project uses data gathered from four main sources:

• UT's IEL Indoor Air Quality (IAQ) Beacon
• Onnela Labs's Beiwe Platform
• Fitbit Wearable Devices gathered on the Fitabase Platform
• Surveys administered by UT's REDCap Platform hosted the by Population Research Center

Other sources of data include:

• Hair and saliva samples
• Home dust samples

Project Organization

├── LICENSE
├── README.md          <- The top-level README for developers using this project.
├── data (not included)
│   ├── external       <- Data from third party sources.
│   ├── interim        <- Intermediate data that has been transformed.
|   ├── purgatory      <- Raw data with inconsistent formatting.
│   ├── processed      <- The final, canonical data sets for modeling.
│   └── raw            <- The original, immutable data dump.
│
├── images             <- Study-related images
│
├── notebooks          <- Jupyter notebooks for the majority of analysis - see readme in the folder for more details
│
├── references         <- Data dictionaries, manuals, and all other explanatory materials - see Wiki too
│
├── reports            <- Generated analysis as HTML, PDF, LaTeX, etc.
│   └── figures        <- Generated graphics and figures to be used in reporting
│
├── src                <- Source code for use in this project.
│   ├── __init__.py    <- Makes src a Python module
│   │
│   ├── data           <- Scripts to download or generate data
│   │   └── make_dataset.py
│   │
│   ├── features       <- Scripts to turn raw data into features 
│   │   └── build_features.py
│   │
│   └── visualization  <- Scripts to create exploratory and results oriented visualizations
│       └── visualize.py
│
└── videos             <- Study-related videos

Contribute

• Issue Tracker: Issues
• Source Code: SRC

Support

If you are having issues, please contact the project author Hagen Fritz
Email: HagenFritz@utexas.edu

License

The project is licensed under the MIT license.

Project based on the cookiecutter data science project template. #cookiecutterdatascience