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Create Datasets, control who can access them, and manage their files, snapshots, and settings. A Dataset always reflects the most recent version of the data. For reproducibility, you can create read-only snapshots of your Dataset at any moment in time. Snapshots are associated with the Dataset they version.

Create a new Dataset

If the Dataset you need is not yet in Domino, you can create it in your Project:
  1. In your Project, go to Data > Domino Datasets > Create New Dataset.
  2. Enter a Dataset Name and Description, then click Next.
  3. Enter the users or organizations to give them permission to the Dataset.
    To give all Project members access to the Dataset, click the Add all project members link.
  4. Specify the user or organization’s role.
  5. Click Add.
  6. Repeat steps 3-5 as needed.
    In the Current Permissions area, you can modify the role as needed, or click the trash icon to delete permissions.
  7. Click Finish.

Create a new Dataset from a snapshot

Snapshots are read-only. To iterate on one, create a new Dataset from it, modify the new Dataset, and take a new snapshot. See Create a new Dataset from a snapshot for the UI, CLI, and API steps.

Upload files to a Dataset

Use the Domino UI to upload up to 50 GB or 50,000 individual files. For larger uploads, use the Domino CLI for your upload.
  1. In your Project, go to Data > Domino Datasets.
  2. Open the Dataset to which you want to add files, then click Upload files: Upload files to a Dataset You can browse your local filesystem or drag and drop files to upload.
    To preserve the filesystem structure of your uploads, use the drag-and-drop option. You can pause and resume the upload as needed.
    Uploading to a folder can fail if you do not have permissions to write to it. For example, a folder created from a Workspace might not be writable through the UI without appropriate changes to permissions.

Download files from Datasets

Use the Domino UI or CLI to download files and folders from your Projects.
  1. In your Project, go to Data > Domino Datasets.
  2. Open the Dataset you want to download files from.
  3. Navigate to the directory where your files are located.
  4. Either:
    • Click the vertical dots next to the file or folder you want to download. Click Download. If you are downloading a folder, the downloaded file is a ZIP or TAR archive, which can be toggled via the Configuration records com.cerebro.domino.dataset.batchDownloadArchiveFormat. Otherwise, the file downloads directly.
    • Click the checkboxes to the left of the files and directories you want to download, and then click Download Selected Items. If you are downloading a folder or multiple files, the downloaded file is a ZIP file (default) or TAR archive, which can be toggled via the Configuration records key com.cerebro.domino.dataset.batchDownloadArchiveFormat. Otherwise, the file downloads directly.

Modify Datasets

You can always modify the contents of a Dataset or rename the Dataset.
Always create a snapshot before modifying the contents of a Dataset so that you can always return to the previous version of the data.

Rename a Dataset

You can change the name of a Dataset.
  1. In the navigation pane, click Data.
  2. Click Domino Datasets.
  3. Click the Dataset to rename.
  4. Go to More Actions > Rename Dataset.
  5. Enter a New Name and click Rename.

Delete a Dataset

If you no longer need the entire Dataset, you can mark it for deletion. When you mark a Dataset for deletion, it removes the Dataset and its associated snapshots from the originating Project and from all projects that it was shared with. Domino executions cannot use the Dataset. A Domino administrator must perform the final deletion.
  1. In the navigation pane, click Data.
  2. Click Domino Datasets.
  3. Click the name of the Dataset to delete.
  4. Go to More Actions > Click Delete Dataset.
  5. Click Delete Dataset to confirm that you want to mark the Dataset for deletion. Your administrator must permanently delete the Dataset.

Add or remove files

You can add or delete files in a Dataset using the Domino UI. With the CLI, you can add all the files in a folder to a Dataset.
In the navigation pane, click Data, then click the name of the Dataset to change.
  • To add files, click Upload files.
  • To delete files, select the files to delete, then click Delete Selected Items.
  • To rename the Dataset, click Rename Dataset, enter the new name, then click Rename.
Before deleting a file with a special character like a backslash () in its name, you need to rename it first. You can use a tilde (~) or colon (:) anywhere in a filename, except at the beginning. If the file that you want to delete has a tilde or colon at the beginning of its name, rename it.

Rename files and folders

You can change the name of the latest version of a file or folder in a Dataset. Domino also does not rename files or folders in snapshots.
You must update references to the original file or folder. If you don’t, your Project might not work. For example, you might see inconsistencies in text files and documentation.
  1. Go to a Project that uses a Dataset.
  2. In the navigation pane, click Data.
  3. To rename the file or folder, go to the end of the row and click the three vertical dots.
  4. Click Rename.
  5. In the Rename window, enter the New Name and click Rename.

Schedule Jobs to update a Dataset

If you have data in an external source from which you want to periodically fetch and load into Domino, you can set up scheduled jobs to write to Datasets. Suppose you have data stored in an external Data Source that is periodically updated. If you wanted to fetch the latest state of that file once a week and load it into a Domino Dataset, you could set up a scheduled Run:
  1. Create a Dataset to store the data from the external source.
  2. Write a script that fetches the data and writes it to the Dataset.
  3. Create a scheduled Job to run your script with the new Dataset configuration. The following is a detailed example showing how to fetch a large, dynamic data file from a private S3 bucket with a scheduled Run once a week.
  4. Create a Dataset to hold the file. This example shows the Dataset named fetched-from-s3. Best practices to fetch Datasets from S3 For this example, assume the S3 bucket is named my_bucket and the file you want is named some_data.csv. You can set up your script like this: fetch-data.py
  5. Set up a scheduled Job that executes this script once a week with the correct Dataset configuration.

Next steps

Last modified on August 6, 2026