Summary and Schedule
One of the primary challenges with the utilization of digital datasets in the social sciences is a lack of data literacy skills in collecting data. This includes both data collection from existing data repositories and field-based data collections such as observation data, interviews, and surveys. This module will provide learning materials on both sides to prepare the researchers with data collection skills at beginner, intermediate, and expert levels.
Getting Started
These modules are intended to be hands-on through the use of Jupyter notebooks. Many of these modules build on concepts and datasets that have been introduced in the Data Collection module. Learners are encouraged to work through those modules first.
| Setup Instructions | Download files required for the lesson | |
| Duration: 00h 00m | 1. Food Deserts |
How can road network analysis be used to determine
accessibility? What data is required to determine food deserts in a region? How does your analysis result compare to USDA’s Food Access Research Atlas data? |
| Duration: 01h 45m | Finish |
The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.
Data Sets
Each lesson will provide instructions on where to access and download the relevant datasets.
Software Setup
Details
We will be utilizing Jupyter notebooks for most of the hands-on activities. A public JupyterHub server has been setup for these lessons, where you can login with your institutional credentials.