Create a new OpenRefine project

OpenRefine works with a variety of file types, including tab separated (tsv), comma separated (csv), Excel (xls, xlsx), JSON, XML, RDF as XML, and Google Spreadsheets. See the OpenRefine Importers page for more information.

Launch OpenRefine

Windows: double-click on the openrefine.exe file. Java services will start automatically on your machine, and OpenRefine will open in your browser. Be sure to use either Chrome or Firefox, as OpenRefine does not play well with Microsoft Edge or Safari.

Mac: OpenRefine can be launched from your Applications folder.

Linux: navigate to your OpenRefine directory in the command line and enter ./refine.

Once OpenRefine is launched in your browser, the home screen displays options to Create Project, Open Project, or Import Project.

Select Create a project.

If launch fails

If OpenRefine does not automatically open within your browser after launch, point your browser at http://127.0.0.1:3333/ or http://localhost:3333 to launch the program.

Note: Keep the terminal window hosting Java open in the background.

Terminal Java — Keep the terminal window open when using OpenRefine

Watch this video on how launch OpenRefine the first time.

Create a Project

Projects can be created in a variety of ways, e.g., by uploading data from your computer or by importing it from a web address.

Create a project by uploading data from your computer

Choose Create Project
Select Get data from this Computer.
Select Choose Files and browse to select the file QldSharkControlProgramCatch_2017.csv you saved to your Downloads folder.
Either click Open or double-click on the filename to import it into OpenRefine.
Click Next.

Create a project by importing the data from a Web Address

Choose Create Project
Click Web addresses (URLs).
When a text box opens, enter this address https://raw.githubusercontent.com/stapletonsl/ClassData2022/master/QldSharkControlProgramCatch_2017.csv
Click Next.

Data preview

OpenRefine gives you a preview to show you how it has interpreted the file you have uploaded or imported. If your data was tab-delimited rather than comma-delimited, the preview might look strange.

Be sure the correct separator is displayed in the box shown.
If you have made any changes, click Update Preview (bottom right).
If the wrong file is displaying, click <<Start Over (upper left).

There are options to indicate whether the dataset has column headers included and whether OpenRefine should skip a number of rows before reading the data.

Choose UTF8 as the method of encoding as this should convert any ‘smart’ formatting into plain text.
Make sure Trim leading & trailing whitespace from strings is checked. This will automatically remove any whitespace from the beginning or end of data strings or cells, making the data computer readible. Words with spaces at the beginning or end are particularly hard for we humans to tell from strings, but the blank characters will make a difference to the computer.
Look at the first 4 lines of the dataset, these contain information about the dataset such as the title, date range location names and a blank row which are not required and mess up the data. Let’s remove these now by checking the box Ignore this and add 4 to the line(s) at beginning of file
Ensure the first row is used to create the column headings by checking the box Parse next 1 line(s) as column headers
Make sure the Attempt to parse cell text into numbers … box is not checked, so OpenRefine doesn’t try to automatically detect numbers. Parsing in this context refers to the way the software will interpret the format of the data.
Give the project a meaningful name such as QLDSharkCaught_2017_v1
If all looks fine, click Create Project.

Create Project — Create a project in OpenRefine

Watch the steps above on this video.

<-- BACK | NEXT -->