{"id":4625,"date":"2026-09-09T16:45:04","date_gmt":"2026-09-09T19:45:04","guid":{"rendered":"https:\/\/ccdhhn.ca\/?post_type=tribe_events&p=4625"},"modified":"2026-09-09T16:45:06","modified_gmt":"2026-09-09T19:45:06","slug":"data-cleaning-with-openrefine","status":"publish","type":"tribe_events","link":"https:\/\/ccdhhn.ca\/fr\/workshop\/data-cleaning-with-openrefine\/","title":{"rendered":"Data Cleaning with OpenRefine"},"content":{"rendered":"
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Format <\/h3>\n\tvirtual\/virtuel<\/div>\n\n\n
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Event Language<\/h3>\n\tEnglish<\/div>\n\n\n
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Cat\u00e9gorie d\u2019\u00c9v\u00e8nement:<\/dt>
1-4 hour workshop<\/a><\/dd><\/div>\n\n\n\n

Researchers and librarians often deal with \u201cmessy\u201d data. This could include inconsistent interview transcripts, poorly formatted longitudinal datasets, or standardizing names for an authority file. Preparing this data for analysis is a critical step that requires the same level of rigor and reproducibility as the analysis itself. This workshop introduces OpenRefine, a powerful, free, and open-source tool for cleaning, normalizing, and transforming research data. participants work with a sample dataset to learn how to efficiently handle common data issues, such as automating data standardization, identifying clusters of similar entries, and transforming complex strings into structured information without the need for advanced programming. Unlike manual editing in Excel, OpenRefine records every step of your process, ensuring your data cleaning is transparent and fully reproducible. Participants should be comfortable using a computer and have a general understanding of spreadsheets. No prior programming experience is necessary.<\/p>\n\n\n

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ACENET<\/a><\/h3>\n\t<\/div>\n\t\t\t\t

View Organisateur Website<\/a><\/p>\n\t\t<\/div>\n\n\n

\n\t\n\t\tWebsite and Registration\t<\/a>\n<\/div>\n\n\n\t
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