Data Carpentry for Social Science Lessons Released

The highly anticipated Data Carpentry lessons for Social Sciences have now been released, and are ready for teaching.

As the first Data Carpentry Curriculum targeted towards researchers outside of the life sciences, the lessons allow us to reach out to new communities. The curriculum covers data organisation in spreadsheets, data cleaning with OpenRefine, as well as data manipulation and visualization with R.

These lessons focus around an interview dataset collected between November 2016 and June 2017 from farmers in Tanzania and Mozambique by researchers in the SAFI (Studying African Farmer-led Irrigation) research project.

This dataset includes information about household features (e.g., construction materials used, number of household members), agricultural practices (e.g., water usage), assets (e.g., number and types of livestock) and household members. You can find more information about this dataset on Figshare.

This curriculum teaches best practices for working with rectangular and tidy data and covers data organization in spreadsheets, data cleaning with OpenRefine, and data manipulation and visualization with R. Lessons for teaching SQL and Python with this dataset will be released at a later point.

Read more about the lesson release.