Data Structure

Teams and Workspaces

1. Automatic Creation at Registration

When a user registers on the Supervisely platform, one Team and one Workspace are automatically created in their account. By default, this workspace is named First Workspace.

This is how it looks on the Supervisely platform:

And this is how it looks schematically:

2. Team & Workspace Structure Rules

Every Member with Full-scope Permission is always a part of at least one Team. A member may leave or delete a personal Team, provided that they remain associated with at least one Team that includes at least one Workspace at all times.

Each Team must always have at least one Workspace, although it doesn't have to be the original one created at registration.

The Supervisely system strictly enforces these rules and will not allow any actions that would violate them. For example, you won’t be able to delete your last remaining Team or its only Workspace.

3. Creating & Managing Teams

A Member with the Admin role can invite other Members to their Team. The invited member will gain access to all projects within this Team.

In addition to their default Team, a Member can also create new Teams to collaborate on separate projects or with different groups.

4. Switching Between Teams

To manage or switch between Teams, click the arrow next to the name of your current Team. A menu will appear with a list of all Teams you are a member of (not necessarily the ones you created) along with other settings.

When you invite other Members to your Team, make sure you have the correct Team selected as active. The invitations will be sent specifically to the currently active Team that you created.

Projects and Datasets

Inside a Workspace, a Member can create an unlimited number of Projects. Each Project can contain multiple Datasets, which store the actual data and annotations.

This flexible structure allows Members to organize data in a way that fits their workflow.

Furthermore, a Member can create additional Workspaces inside any Team where they have the Admin role. Inside a Dataset, you can create Sub-Datasets, enabling flexible and deeply nested data structures — just like folders and subfolders on your computer. There are no limitations on nesting depth, so you can organize your data in whatever hierarchy makes sense for your workflow.

Let’s repeat an important rule: at the Project level, you cannot store files directly — only Datasets can exist there. Files and Sub-Datasets can only be added inside a Dataset.

You can think of Datasets as folders and Sub-Datasets as subfolders. This allows you to recreate complex directory structures exactly the way you organize data on your local machine or in your company’s cloud storage. It’s especially useful if you’re working with a shared storage system that already follows a specific hierarchy — you can mirror that same structure inside Supervisely without restrictions.

To create a sub-dataset inside an existing dataset:

1. Click the Add button

2. Select Create New Dataset Then, you can navigate into the newly created sub-dataset and upload your files there.

Great! Your sub-dataset with files is now ready.

Project versions

Data Versioning allows you to manage and track different versions of a project over time. It allows you to save, restore, and compare different states of a project.

Key features of project versioning include:

• Version Control: Track and manage changes made to the project over time, ensuring every specific state is recorded.

• History Tracking: Maintain a comprehensive history of all modifications, making it easy to understand the project's evolution.

• Reverting Changes: Restore any previous version of the project, allowing you to get a new project with a specific state of data.

• MLOps Execution: Execute machine learning tasks on specific versions of the project data, ensuring that the exact state of the data used is known. This guarantees consistency and reproducibility of results.