Data cleaning is an important step in any data-driven research project. Often data is harvested from diverse sources such as the web, databases, spreadsheets, text files, and countless other places. These sources can employ different encodings, formats, and follow different conventions all of which must be normalized before analysis can take place. Exactly what steps must be taken to clean a dataset depends on the data involved and the type of analysis being conducted. OpenRefine is a tool designed to make data cleaning easy. In this workshop we will learn how to use OpenRefine to clean a dataset as well as talk generally about the process of data cleaning.