Edit Files
Edit File Metadata
Go to the dataset you would like to edit where you will see the listing of files. Select the files you would like to edit by using either the “Select All” checkbox or individually selecting files. Next, click on the “Edit Files” button above the filetable and from the dropdown menu select if you would like to:
- Delete the selected files
- Edit the file metadata (file name, description) for the selected files
- Restrict the selected files
- Unrestrict the selected files (only if the selected files are restricted)
- Add tags to the selected files
You will not have to leave the dataset page to complete these action, except for editing file metadata, which will bring you to the Edit Files page. There you will have to click the “Save Changes” button to apply your edits and return to the dataset page.
If you restrict files, you will also prompted with a popup asking you to fill out the Terms of Access for the files. If Terms of Access already exist, you will be asked to confirm them.
File Path
The File Path metadata field is a Dataverse installation’s way of representing a file’s location in a folder structure. When a user uploads a .zip file containing a folder structure, the Dataverse installation automatically fills in the File Path information for each file contained in the .zip. If a user downloads the full dataset or a selection of files from it, they will receive a folder structure with each file positioned according to its File Path. Only one file with a given path and name may exist in a dataset. Editing a file to give it the same path and name as another file already existing in the dataset will cause an error.
A file’s File Path can be manually added or edited on the Edit Files page. Changing a file’s File Path will change its location in the folder structure that is created when a user downloads the full dataset or a selection of files from it.
If there is more than one file in the dataset, and once at least one of them has a non-empty directory path, the Dataset Page will present an option for switching between the traditional table view, and the tree-like view of the files showing the folder structure, as in the example below:
File Tags
File Tags are comprised of custom, category (i.e. Documentation, Data, Code) and tabular data tags (i.e. Event, Genomics, Geospatial, Network, Panel, Survey, Time Series). Use the dropdown select menus as well as the custom file tag input to apply these tags to the selected files. There is also a Delete Tags feature that, if checked, will allow you to delete unused file tags within that dataset.
Replace Files
In cases where you would like to revise an existing file rather than add a new one, you can do so using our Replace File feature. This will allow you to track the history of this file across versions of your dataset, both before and after replacing it. This could be useful for updating your data or fixing mistakes in your data. Because replacing a file creates an explicit link between the previous dataset version and the current version, the file replace feature is not available for unpublished dataset drafts. Also note that replacing a file will not automatically carry over that file’s metadata, but once the file is replaced then its original metadata can still be found by referencing the previous version of the file under the “Versions” tab of the file page.
To replace a file, go to the file page for that file, click on the “Edit File” button, and from the dropdown list select “Replace”. This will bring you to the Replace File page, where you can see the metadata for the most recently published version of the file and you can upload your replacement file. Once you have uploaded the replacement file, you can edit its name, description, and tags. When you’re finished, click the “Save Changes” button.
After successfully replacing a file, a new dataset draft version will be created. A summary of your actions will be recorded in the “Versions” tab on on both the dataset page and file page. The Versions tab allows you to access all previous versions of the file across all previous versions of your dataset, including the old version of the file before you replaced it.