Open Refine for Ecology

Exporting and Saving Data from OpenRefine


Teaching: 10 min
Exercises: 5 min
  • How can we save and export our cleaned data from OpenRefine?

  • Save an OpenRefine project.

  • Export cleaned data from an OpenRefine project.


Saving and Exporting a Project

In OpenRefine you can save or export the project. This means you’re saving the data and all the information about the cleaning and data transformation steps you’ve done. Once you’ve saved a project, you can open it up again and be just where you stopped before.


By default OpenRefine is saving your project. If you close OpenRefine and open it up again, you’ll see a list of your projects. You can click on any one of them to open it up again.


You can also export a project. This is helpful, for instance, if you wanted to send your raw data and cleaning steps to a collaborator, or share this information as a supplement to a publication.

  1. Click the Export button in the top right and select Export project.
  2. A tar.gz file will download to your default Download directory. The tar.gz extension tells you that this is a compressed file. Which means that this file contains multiple files. You can double-click on the tar.gz file and it will expand into a directory. A folder icon will now appear.
  3. Look at the files that appear in this folder. What files are here? What information do you think these files contain?


You should see:

You can import an existing project into OpenRefine by clicking Open... in the upper right > Import Project and selecting the tar.gz project file. This project will include all of the raw data and cleaning steps that were part of the origina project.

Exporting Cleaned Data

You can also export just your cleaned data, rather than the entire project.

  1. Click Export in the top right and select the file type you want to export the data in. Tab-separated values (tsv) or Comma-separated values (csv) would be good choices.
  2. That file will be exported to your default Download directory. That file can then be opened in a spreadsheet program or imported into programs like R or Python, which we’ll be discussing later in our workshop.

Remember from our lesson on Spreadsheets that using widely-supported, non-proprietary file formats like tsv or csv improves the ability of yourself and others to use your data.

Key Points