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Data-Management

A tutorial on data-management basics using OpenRefine. Adapted from a 2017 Data Managment workshop designed by Rachael Starry and the tri-cods tidy-data workshop.

As scholars seeking to use digital methods in our research, we need to understand how we can make both quantitative and qualitative data machine-readable and machine-usable. But what is data anyway? What is a dataset? Where can we find raw data? How do we know whether our data is "clean" or "dirty"? How can we clean "dirty" data? These are a few of the questions which this workshop sets out to address.

Learning Goals

  • Understand the structure and appearance of datasets
  • Discover where and how to find data online
  • Apply learned concepts in order to clean raw datasets in OpenRefine

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Learning Path

Thinking About Data

Finding Data

Messy & Tidy Data

Introduction to OpenRefine

Data Cleaning


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