An Introduction to OpenRefine

Clean Up Your Messy Data:
Munging and Cleansing Using OpenRefine

This workshop focusses on OpenRefine and provides two tutorials to explore how cleaning, transforming it from one format into another; and extending it with web services and external data can enhance its usefulness for scholarly analysis.

Tutorial 1:  Introduction to OpenRefine

Tutorial 2: Taking OpenRefine a Step Further

Each of these tutorials provides steps and access to sample data for use during the workshop.

The presentation deck is also available.

There are a variety of other tools that may or may not be mentioned but are worth knowing about in the context of today’s discussion.

1. Trifacta Data Wrangler (Only in Chrome)
2. How to clean your data for DataWrapper
3. Mr Data Converter
4. RapidMiner
5. Dataiku Data Science Studio
6. Tableau
7. Google FusionTables (Gone :-()

Additional sources of information about OpenRefine:

1. OpenRefine web site
2. OpenRefine Documentation for Users
3. OpenRefine documentation Wiki site
4. Using OpenRefine book by Ruben Verborgh, Max De Wilde and Aniket Sawant
5. OpenRefine history from Wikipedia

Additional Resources of Note from earlier Data Munging Exercises and Workshops (archive / legacy):

1. Google Solve for X
2. Google Research
   1. SketchUp!
3. Google Scholar
   1. ResearchGate
   2. Academia.edu
4. Google Keep
   1. Evernote
5. Google Public Data Explorer
6. Google Developers
7. IBM Watson
8. Google Groups
9. Google Cultural Institute
10. Google NGram Viewer
11. Google Books
12. Google Trends
13. Google Trends Visualiser
14. Google Correlate
15. Google Gap Minder (Hans Rosling: New Insights on Poverty)
16. Google Docs Extended/Secrets
    1. SurveyMonkey
    2. LimeSurvey
17. Google BigPicture Group
18. Google Analytics
19. Google Apps
20. Evolution of the Web
21. Google Time

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