OpenRefine Lessons for Librarians: Reference

Key Points

Introduction to OpenRefine	OpenRefine is 'a tool for working with messy data' OpenRefine works best with data in a simple tabular format OpenRefine can help you split data up into more granular parts OpenRefine can help you match local data up to other data sets OpenRefine can help you enhance a data set with data from other sources
Importing data into OpenRefine	Use the 'Create Project' option to import data You can control how data imports using options on the import screen
Basic OpenRefine functions I: Working with columns, sorting, faceting, filtering and clustering	You can reorder, rename and remove columns in OpenRefine You can use facets and filters to explore your data You can use facets and filters work with a subset of data in OpenRefine You can easily correct common data issues using Facets and Clustering
Basic OpenRefine functions II:	You can alter data in OpenRefine based on specific instructions You can expand the data editing functions that are built-in into OpenRefine by building your own
Advanced OpenRefine functions	OpenRefine can look up custom URLs to fetch data based on what's in an OpenRefine project Such API calls can be custom built, or one can use existing Reconciliation services to enrich data OpenRefine can be further enhanced by installing extensions

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