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This guide covers best practices for organizing and managing datasets in Avala.

Organization Strategies

By Project

Organize datasets by the project they belong to:
  • Group related data together
  • Use clear naming conventions
  • Add descriptions for context

By Data Type

Separate datasets by data format:
  • Images for 2D annotation
  • Point clouds for 3D annotation
  • Video sequences

By Stage

Track data through your pipeline:
  • Raw uploads
  • In progress (being annotated)
  • Completed (ready for training)

Tagging Best Practices

Use consistent tags for easy filtering:

Search and Filter

Avala supports powerful search:

Search Operators

  • field:value - Exact match
  • "quoted phrase" - Phrase match
  • -term - Exclude term

Filterable Fields

Bulk Operations

Select multiple datasets for bulk actions:
  • Bulk tag: Add or remove tags from many datasets
  • Bulk delete: Remove datasets (with confirmation)
  • Bulk visibility: Change visibility settings

Dataset Settings

Visibility

Datasets default to Private. Supporting deployments also offer Unlisted for bounded known-link previews and Public for public discovery. Unlisted does not grant editing, workforce, or raw-download rights and does not bypass private owner visibility. See the visibility guide for the complete sharing contract and deployment caveats.

Collaborators

Add team members who can view or edit your dataset:
  1. Go to dataset Settings
  2. Click Add Collaborator
  3. Search for user by username or email
  4. Set permission level

Best Practices

  1. Use descriptive names: “Training Images Batch 3” is better than “data”
  2. Add descriptions: Help teammates understand the dataset contents
  3. Tag consistently: Establish tagging conventions for your team
  4. Archive completed work: Move finished datasets to archive to keep workspace clean