Datasets overview

Understand datasets as reusable, versioned membership definitions.

A Unitlab dataset names a reusable membership definition. Publishing a version freezes the exact source membership so projects, automation, and downstream records can refer to the same cohort.

Use this area when: a curated cohort must be reused, compared over time, attached to projects, or reproduced later.

How this area fits into production

Unitlab datasets overview

The dataset list is the starting point for ownership, current version, lifecycle, and reuse—not the place where project task state is managed.

What this area controls

What a dataset is

A Unitlab dataset is a curated collection built from folders or individual assets. The live dataset table shows:

• name;

• version;

• asset count;

• size;

• data type;

• projects using the dataset;

• last modified date;

• creator.

Datasets can contain image, video, or multimodal data. Dataset lifecycle tabs include Active, Archived, and Trash.

Version-first behavior

The SDK describes datasets as version-first:

1. Create a dataset from selected folders or assets.

2. Make edits, which appear as unpublished changes.

3. Publish a named version to freeze a snapshot.

4. Attach the latest or an exact version to a project.

This distinction prevents a project from silently changing when someone adds new assets to the working dataset. An exact attachment can reference, for example, dataset version 2 rather than “whatever the dataset contains today.”

The current model is:

Folders and assets
        ↓
Mutable dataset working draft
        ↓ Publish version
Immutable DatasetVersion
        ↓ Attach
Independent project copy

There is no Sync, Ignore, or Auto-Sync action between a project and an attached Data Assets source. Editing the source after attachment does not alter the project. To adopt the change, the user publishes a newer dataset version and attaches that version.

Datasets-list UX

The standalone Datasets page includes search, New Dataset, Active/Archived/Trash views, pagination, row selection, and a table with:

• Name;

• Version;

• Assets;

• Size;

• Data Type;

• Used in;

• Last Modified;

• Created By;

• Actions.

The Version cell is an orange Draft vN pill when publishing would create the next version, or a blue vN pill when the working draft matches the latest published version. Mixed-family datasets display Multimodal.

Row actions adapt to lifecycle state. Active datasets can be renamed, have files added, attach a published version to a project, archive, or move to Trash. Archived datasets can be restored to Active or trashed. Trash supports Restore or Delete forever. Dataset lifecycle changes affect the dataset and its versions/memberships; they do not archive or delete the underlying folders and assets.

Start with the right page

Decision	Production guidance
Create membership	Create a dataset from an inspected Data Space cohort.
Freeze membership	Publish a dataset version.
Use in production	Attach the intended version to a project.
Audit change	Review dataset history and project dependencies.

Operating boundary

• A dataset is not a folder; folders organize source.

• A dataset is not a project; projects operate work.

• A dataset is not a release; releases freeze downstream output.

A production-ready handoff

The published version has a clear purpose, owner, exact membership, source provenance, and a reviewed relationship to every attached project.

Product context

Unitlab helps AI teams curate, annotate, manage, version, and prepare multimodal training data at enterprise scale.

See Unitlab Dataset Management for the commercial overview and multimodal data annotation for upstream labeling workflows.

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Explore related Unitlab capabilities: multimodal data curation