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

# Data Organization

- [Core concepts](https://docs.supervisely.com/data-organization/overview.md)
- [Project and Dataset](https://docs.supervisely.com/data-organization/project-dataset.md)
- [Create](https://docs.supervisely.com/data-organization/project-dataset/create.md): This article provides a step-by-step guide to creating classes and tags: how to define them in the project before annotation and how to add them directly in the labeling tools.
- [Data Structure](https://docs.supervisely.com/data-organization/project-dataset/data-structure.md): This article explains the Data structure in Supervisely, including how Projects, Datasets, and Files are organized in Team and Workspace. Learn how to navigate, manage, and structure your data.
- [Define Classes & Tags](https://docs.supervisely.com/data-organization/project-dataset/define-classes-tags.md): This article explains how to create and manage classes and tags for data annotation in the Labeling Tool to ensure structured and consistent labeling within a project.
- [Gallery & Table views](https://docs.supervisely.com/data-organization/project-dataset/gallery-table-views.md): This article is about how gallery and table views let you customize data display: gallery provide a quick visual overview, while tables offer detailed, sortable comparisons.
- [Collections](https://docs.supervisely.com/data-organization/project-dataset/collections.md): Collections are custom selections of data within a project. They enable flexible filtering and control over annotation workflows.
- [Project Versions](https://docs.supervisely.com/data-organization/project-dataset/project-versions.md): Learn how to use Project Versions in Supervisely. Save, restore, and track project states, instantly preview data, and visualize data evolution with MLOps Workflow.
- [AI Search](https://docs.supervisely.com/data-organization/project-dataset/ai-search.md): This article is about AI Search, which quickly finds images using semantic similarity powered by CLIP. It supports prompt-based and diverse search modes with automatic embedding updates.
- [Quality Assurance & Statistics](https://docs.supervisely.com/data-organization/project-dataset/quality-assurance-and-statistics.md): Understanding your data's characteristics is a key aspect of data preparation. The Statistics section provides tools for data analysis, calculation of statistical metrics and data visualization.
- [Practical applications of statistics](https://docs.supervisely.com/data-organization/project-dataset/quality-assurance-and-statistics/practical-applications-of-statistics.md): Learn how to use best quality assurance and interactive statistical tools to perfect your custom training datasets and improve neural network performance.
- [Project Settings](https://docs.supervisely.com/data-organization/project-dataset/project-settings.md): Configure project-level settings in Supervisely, including the labeling interface and Read-only mode to protect your data from accidental changes.
- [Advanced](https://docs.supervisely.com/data-organization/project-dataset/advanced.md)
- [Custom Data](https://docs.supervisely.com/data-organization/project-dataset/advanced/custom-data.md): Explore how to store and manage technical metadata, configurations, and integration settings using Custom Data in JSON format.
- [Validation Schemas](https://docs.supervisely.com/data-organization/project-dataset/advanced/validation-schemas.md)
- [MLOps Workflow](https://docs.supervisely.com/data-organization/mlops-workflow.md): The main features, capabilities and usage recommendations of MLOps Workflow are described in this documentation.
- [Team Files](https://docs.supervisely.com/data-organization/team-files.md)
- [Disk usage & Cleanup](https://docs.supervisely.com/data-organization/storage.md)
- [Operations with Data](https://docs.supervisely.com/data-organization/operations-with-data.md)
- [Data Filtration](https://docs.supervisely.com/data-organization/operations-with-data/data-filtration.md): Filter, create records, and process information with confidence. Your data is always under your control.
- [How to use advanced filters](https://docs.supervisely.com/data-organization/operations-with-data/data-filtration/how-to-use-advanced-filters.md)
- [Pipelines](https://docs.supervisely.com/data-organization/operations-with-data/pipelines.md): Easily combine data management, augmentation, filtering, and neural network operations with drag-and-drop pipelines, which include a set of over 150 nodes for different modalities.
- [Augmentations](https://docs.supervisely.com/data-organization/operations-with-data/augmentations.md)
- [Splitting data](https://docs.supervisely.com/data-organization/operations-with-data/splitdata.md)
- [Converting data](https://docs.supervisely.com/data-organization/operations-with-data/overview.md)
- [Convert to COCO](https://docs.supervisely.com/data-organization/operations-with-data/overview/to_coco.md)
- [Convert to YOLO](https://docs.supervisely.com/data-organization/operations-with-data/overview/to_yolo.md)
- [Convert to Pascal VOC](https://docs.supervisely.com/data-organization/operations-with-data/overview/to_pascal_voc.md)
- [Data Commander](https://docs.supervisely.com/data-organization/data-commander.md)
- [Clone Project Meta](https://docs.supervisely.com/data-organization/data-commander/clone-meta.md)