> For the complete documentation index, see [llms.txt](https://docs.unitlab.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.unitlab.ai/documentation/data/data-curation.md).

# Data curation

Curation happens inside a Data Space folder. Explore resolves candidates with structured filters, visual views, and frame granularity; Collections save reviewed subsets inside that folder for later comparison, attachment, or dataset creation.

### Before you make the change

* Open the exact source folder—not the workspace-level Assets landing page.
* Write the cohort question and representative inclusion and exclusion examples.
* Decide whether the unit is a whole asset or an individual video frame before selecting files.

### Follow the interface

#### Curate inside the source folder

![Folder Explore view with List, Grid, Embedding, Collections, and advanced filters](https://292810646-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FGjVLUz4wthGkGlRKM6rM%2Fuploads%2FfX5Z84BKLX5ApgwTJhjt%2Fdata-curation-folder.png?alt=media\&token=f245cb7d-56f2-4067-8e7d-488392b97945)

*Inside a folder, Explore combines List, Grid, and Embedding views with asset type, granularity, source, tag, date, size, and dimension filters. The live result count is the scope of the next selection.*

Choose Video to curate whole video assets or Frames to expand videos into frame-level candidates. Filters narrow the current view; they do not create durable membership by themselves.

#### Save reviewed subsets as Collections

![Folder Collections tab and empty-state creation guidance](https://292810646-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FGjVLUz4wthGkGlRKM6rM%2Fuploads%2FZRsXgyjO7I7FQXtO6Dr7%2Fdata-collections.png?alt=media\&token=f20c12b6-b645-4705-8708-76f90c33a168)

*Collections belong to the current folder. Select files in Explore and use Add to Collections; then open Collections to review the saved subset and its item count.*

A Collection is useful for working cohorts and repeated inspection. Use a dataset version when membership must become an immutable, reusable production input.

#### Use embeddings as evidence, not as labels

![Embedding exploration view](https://292810646-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FGjVLUz4wthGkGlRKM6rM%2Fuploads%2FM33ZXW6TSC2jKQyQMrna%2Fembedding-view.png?alt=media\&token=ad43e6e5-800c-43e8-a62e-a5a46dd0afff)

*Embedding view exposes clusters, gaps, duplicates, and outliers within the current folder. Human review determines whether proximity is relevant to the cohort decision.*

### Understand the product behavior

The **More Filters** sidebar is available from the Assets and Folders tabs and remains available inside folder detail. Its fixed sections are:

* **Asset Type:** Image, Video, Audio, Text, Medical, and Document;
* **Source:** Uploaded or Cloud storage;
* **Tags:** searchable tag selection;
* **Date:** asset creation date;
* **File Properties:** minimum/maximum size and minimum width/height.

The header badge counts active filter groups. The footer continuously reports the matching result count and displays **Updating…** while a new result set is loading. Added filters provide controls appropriate to their value: text operators, date or date-range inputs, boolean toggles, multiselect chips, color swatches, numeric range sliders, and searchable entity pickers for users, tags, folders, and datasets.

The complete additional-filter catalog is organized as follows:

| Category           | Filter groups and fields                                                                                                                                                                                                                            |
| ------------------ | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| **Data**           | File name, file type, extension, MIME type, asset ID; upload/created/modified/last-synced dates; width, height, resolution, aspect ratio, file size; video duration, frame count, FPS; medical modality, series count, study count, and slice count |
| **Metadata**       | Folder, subfolder, collection, dataset membership, sequence membership, group membership; storage provider, bucket, import source, data source; uploaded by, created by, updated by; asset and system tags                                          |
| **Embeddings**     | Similar assets/images/frames; text-to-image and natural-language search; embedding cluster and cluster membership; diverse and representative samples; similarity and distance thresholds                                                           |
| **Image Features** | Sharpness, noise level, exposure; brightness, contrast, saturation, dominant colors; entropy, complexity, texture density, edge density; orientation, foreground coverage, and background coverage                                                  |
| **Video & Frames** | Frame number, timestamp, keyframes only; scene changes, shot boundaries, segments; frame tags, frame attributes, and frame quality                                                                                                                  |
| **Data Quality**   | Exact and near duplicates; outliers and anomalies; blurry, low-resolution, corrupted, and incomplete assets; missing, invalid, and empty metadata                                                                                                   |
| **Search**         | Metadata search, tag search, natural-language query, and embedding search                                                                                                                                                                           |

Filters that operate on stored asset fields and computed metrics narrow the results immediately. These include extension, MIME type, asset ID, uploaded/created/modified dates, creator, orientation, low resolution, blurry assets, dominant color, duration, frame count, FPS, series/slice count, and numeric image-curation metrics. Catalog entries carrying a **Preview** badge can be configured in the interface but do not yet narrow the result set.

On the Folders tab, an active asset filter keeps a folder only when its subtree contains at least one matching asset. Filters run before duplicate source identities are collapsed, so matching behavior remains stable across project clones of the same underlying data.

Typical curation flows include finding low-resolution uploads, isolating studies from one source bucket and date range, locating long videos, selecting a brightness or sharpness range, finding duplicate-heavy regions, and building a balanced sample from embedding clusters.

Folders preserve source organization rather than label truth. A folder such as `warehouse-camera-07` describes provenance; a decision such as `forklift_present` belongs in an ontology or annotation.

### Folder Explore, Collections, and frame granularity

Folder detail includes **Explore** and **Collections**:

* **Explore** is the normal list/grid/embedding file browser.
* **Collections** stores static, folder-scoped curated file sets.

Selecting files or child folders in Explore enables **Add to Collections** or **Remove from Collections**. A new collection can be created with the current selection, or the selection can be added to an existing collection. Collection actions include View in explorer, Add to dataset, and Download. Removing or deleting a collection never deletes its files.

For video folders, Explore can switch between **Video** and **Frames** granularity:

* **Video** shows one entry per source file and keeps the standard List/Grid/Embedding view switcher.
* **Frames** expands videos with extracted-frame metadata into a paginated frame-card sequence. The breadcrumb reports the frame count and the normal view switcher is disabled while frame browsing is active.
* Native videos without extracted frame metadata appear as one poster entry.
* Selection remains file-level: selecting any frame selects its parent video and highlights all visible sibling frames. Collection, dataset, download, and bulk actions therefore operate on the complete video rather than an arbitrary frame subset.

Inside a collection-scoped Explore view, search and advanced filters continue to apply. A dismissible collection chip identifies the active scope.

### Custom metadata and tags

Tags and custom metadata allow source facts to travel with assets. Appropriate metadata includes capture site, sensor, acquisition date, device version, customer partition, consent state, or study identifier. It should not silently encode ground truth that annotators are expected to determine from the data.

The SDK supports setting custom metadata during upload and updating it later, including explicitly setting it to `null`.

### Build a reviewable cohort

{% stepper %}
{% step %}

#### 1. Open the folder

Navigate Data Space › Assets, open the folder that owns the source cohort, and stay on Explore.
{% endstep %}

{% step %}

#### 2. Choose asset or frame granularity

Keep Video for whole-video decisions or choose Frames when the collection is explicitly frame-level.
{% endstep %}

{% step %}

#### 3. Apply advanced filters

Combine asset type, source, tags, date, size, and dimensions; confirm the result count before selection.
{% endstep %}

{% step %}

#### 4. Inspect across views

Use List for fields and bulk scope, Grid for visual QA, and Embedding for distribution, similarity, and outliers.
{% endstep %}

{% step %}

#### 5. Create a Collection

Select the reviewed items in Explore, choose Add to Collections, create or select the named Collection, then verify it in the Collections tab.
{% endstep %}

{% step %}

#### 6. Promote durable membership

Create a dataset from the approved folder, Collection, assets, or groups when the cohort must be versioned and reused.
{% endstep %}
{% endstepper %}

### Decisions that affect production

| Decision          | Production guidance                                                                                                          |
| ----------------- | ---------------------------------------------------------------------------------------------------------------------------- |
| Filter result     | Temporary query state; record the conditions when they matter to a review.                                                   |
| Collection        | Named folder-scoped working subset for review and reuse during curation.                                                     |
| Dataset version   | Immutable production membership for projects, automation, and provenance.                                                    |
| Frame granularity | Changes the unit selected from video; decide before creating the Collection.                                                 |
| Metadata or tag   | Use durable source/business context and controlled operational categories; keep annotation outputs in the ontology contract. |

### Continue the operating flow

* Create Data Groups before versioning when multiple files form one work unit.
* Create and inspect the dataset membership.
* Attach the explicit dataset version to a project.