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.
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
├── 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
If you are having issues, please contact the project author Hagen Fritz
Email: [email protected]
The project is licensed under the MIT license.
Project based on the cookiecutter data science project template. #cookiecutterdatascience