This is the first Data Carpentry Curriculum to be released targeted towards researchers outside of the life sciences and is still in beta - it would be great if experienced social scientists can review the lessons and provide feedback. The curriculum is focused on best practices for working with rectangular and tidy data and covers data organization in spreadsheets, data cleaning with OpenRefine, as well as data manipulation and visualization with R. There are also lessons on SQL and Python that are available but are not part of this initial release.
As with other materials for Data Carpentry, the same dataset is used across all the lessons. Here, we use a simplified version of a research datasets generated by the SAFI Studying African Farmer-led Irrigation research project. This dataset is available on Figshare and is survey data relating to households and agriculture in Tanzania and Mozambique. The survey data was collected through interviews conducted between November 2016 and June 2017 and covered such things as 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 details about the household members.