Create a dataset
Create a named reusable cohort from validated assets or Data Groups.
Create a named reusable cohort from validated assets or Data Groups.
Create the dataset only after the candidate membership has been inspected. The dataset name and description should communicate why the cohort exists—not merely repeat its source folder.
Confirm the membership question and owner.
Resolve invalid, duplicate, or incomplete grouped items according to policy.
Choose a naming and versioning convention that downstream teams can interpret.

From Data Space › Datasets, choose New Dataset, name and describe the reusable cohort, then attach the exact Folders or Assets that passed curation. Source count is visible before creation.
The user selects New Dataset.
The user enters a name and optional description.
The user chooses at least one folder or asset from the lazy-loaded, server-searched source picker.
Unitlab creates the mutable working draft.
The dataset detail page opens with its folders and assets.
The user publishes v1 before the dataset can be attached to a project.
Adding files to an existing dataset adds existing workspace folders/assets to the working draft. It is not an upload-directly-into-dataset operation.
Name
Use a durable purpose-oriented name; keep environment and date in version metadata where possible.
Owner
Assign a role accountable for membership and version changes.
Source scope
Keep enough provenance to explain every member later.
Groups
Include the grouped unit when project work requires shared context.
Publish the first dataset version.
Attach the exact version to a pilot project.
Record future additions as a new version rather than silently changing history.
Related Unitlab capability guides: training-data curation workflows