[DOCS] Menu Restructuring for 2025 - pass 5 (#28748)

Moving `Compatibility and Support` and `Tool Ecosystem` sections in menu.
openvinotoolkit · Jan 30, 2025 · 9930aea · 9930aea
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diff --git a/docs/articles_en/about-openvino.rst b/docs/articles_en/about-openvino.rst
@@ -7,7 +7,7 @@ About OpenVINO
 
    about-openvino/key-features
    about-openvino/performance-benchmarks
-   about-openvino/compatibility-and-support
+   OpenVINO Ecosystem <about-openvino/openvino-ecosystem>
    about-openvino/contributing
    Release Notes <about-openvino/release-notes-openvino>
 
@@ -42,8 +42,8 @@ Along with the primary components of model optimization and runtime, the toolkit
 * `Neural Network Compression Framework (NNCF) <https://github.com/openvinotoolkit/nncf>`__ - a tool for enhanced OpenVINO™ inference to get performance boost with minimal accuracy drop.
 * :doc:`Openvino Notebooks <get-started/learn-openvino/interactive-tutorials-python>`- Jupyter Python notebook, which demonstrate key features of the toolkit.
 * `OpenVINO Model Server <https://github.com/openvinotoolkit/model_server>`__ - a server that enables scalability via a serving microservice.
-* :doc:`OpenVINO Training Extensions  <documentation/openvino-ecosystem/openvino-training-extensions>` – a convenient environment to train Deep Learning models and convert them using the OpenVINO™ toolkit for optimized inference.
-* :doc:`Dataset Management Framework (Datumaro) <documentation/openvino-ecosystem/datumaro>` - a tool to build, transform, and analyze datasets.
+* :doc:`OpenVINO Training Extensions  <about-openvino/openvino-ecosystem/openvino-training-extensions>` – a convenient environment to train Deep Learning models and convert them using the OpenVINO™ toolkit for optimized inference.
+* :doc:`Dataset Management Framework (Datumaro) <about-openvino/openvino-ecosystem/datumaro>` - a tool to build, transform, and analyze datasets.
 
 Community
 ##############################################################

diff --git a/...s_en/documentation/openvino-ecosystem.rst → ..._en/about-openvino/openvino-ecosystem.rst b/...s_en/documentation/openvino-ecosystem.rst → ..._en/about-openvino/openvino-ecosystem.rst
@@ -68,7 +68,7 @@ without the need to convert.
 
 | **OpenVINO Training Extensions**
 | :bdg-link-dark:`Github <https://github.com/openvinotoolkit/training_extensions>`
-  :bdg-link-success:`Overview Page <https://docs.openvino.ai/2025/documentation/openvino-ecosystem/openvino-training-extensions.html>`
+  :bdg-link-success:`Overview Page <https://docs.openvino.ai/2025/about-openvino/openvino-ecosystem/openvino-training-extensions.html>`
 
 A convenient environment to train Deep Learning models and convert them using the OpenVINO™
 toolkit for optimized inference.
@@ -77,7 +77,7 @@ toolkit for optimized inference.
 
 | **OpenVINO Security Addon**
 | :bdg-link-dark:`Github <https://github.com/openvinotoolkit/security_addon>`
-  :bdg-link-success:`User Guide <https://docs.openvino.ai/2025/documentation/openvino-ecosystem/openvino-security-add-on.html>`
+  :bdg-link-success:`User Guide <https://docs.openvino.ai/2025/about-openvino/openvino-ecosystem/openvino-security-add-on.html>`
 
 A solution for Model Developers and Independent Software Vendors to use secure packaging and
 secure model execution.
@@ -86,7 +86,7 @@ secure model execution.
 
 | **Datumaro**
 | :bdg-link-dark:`Github <https://github.com/openvinotoolkit/datumaro>`
-  :bdg-link-success:`Overview Page <https://docs.openvino.ai/2025/documentation/openvino-ecosystem/datumaro.html>`
+  :bdg-link-success:`Overview Page <https://docs.openvino.ai/2025/about-openvino/openvino-ecosystem/datumaro.html>`
 
 A framework and a CLI tool for building, transforming, and analyzing datasets.
 |hr|

diff --git a/...mentation/openvino-ecosystem/datumaro.rst → ...-openvino/openvino-ecosystem/datumaro.rst b/...mentation/openvino-ecosystem/datumaro.rst → ...-openvino/openvino-ecosystem/datumaro.rst
diff --git a/...no-ecosystem/openvino-security-add-on.rst → ...no-ecosystem/openvino-security-add-on.rst b/...no-ecosystem/openvino-security-add-on.rst → ...no-ecosystem/openvino-security-add-on.rst
diff --git a/...penvino-ecosystem/openvino-test-drive.rst → ...penvino-ecosystem/openvino-test-drive.rst b/...penvino-ecosystem/openvino-test-drive.rst → ...penvino-ecosystem/openvino-test-drive.rst
diff --git a/...cosystem/openvino-training-extensions.rst → ...cosystem/openvino-training-extensions.rst b/...cosystem/openvino-training-extensions.rst → ...cosystem/openvino-training-extensions.rst
diff --git a/...ticles_en/about-openvino/performance-benchmarks/getting-performance-numbers.rst b/...ticles_en/about-openvino/performance-benchmarks/getting-performance-numbers.rst
@@ -165,7 +165,7 @@ as:
    benchmark_app -m <model> -d <device> -i <input>
 
 
-Each of the :doc:`OpenVINO supported devices <../compatibility-and-support/supported-devices>`
+Each of the :doc:`OpenVINO supported devices <../../documentation/compatibility-and-support/supported-devices>`
 offers performance settings that contain command-line equivalents in the Benchmark app.
 
 While these settings provide really low-level control for the optimal model performance on a

diff --git a/...rticles_en/about-openvino/performance-benchmarks/performance-benchmarks-faq.rst b/...rticles_en/about-openvino/performance-benchmarks/performance-benchmarks-faq.rst
@@ -97,7 +97,7 @@ Performance Information F.A.Q.
 
    Intel partners with vendors all over the world. For a list of Hardware Manufacturers, see the
    `Intel® AI: In Production Partners & Solutions Catalog <https://www.intel.com/content/www/us/en/internet-of-things/ai-in-production/partners-solutions-catalog.html>`__.
-   For more details, see the :doc:`Supported Devices <../compatibility-and-support/supported-devices>` article.
+   For more details, see the :doc:`Supported Devices <../../documentation/compatibility-and-support/supported-devices>` article.
 
 
 .. dropdown:: How can I optimize my models for better performance or accuracy?

diff --git a/docs/articles_en/documentation.rst b/docs/articles_en/documentation.rst
@@ -13,18 +13,18 @@ Documentation
 
    API Reference <api/api_reference>
    OpenVINO IR format and Operation Sets <documentation/openvino-ir-format>
-   Tool Ecosystem <documentation/openvino-ecosystem>
+   Compatibility and Support <documentation/compatibility-and-support>
+   Legacy Features <documentation/legacy-features>
    OpenVINO Extensibility <documentation/openvino-extensibility>
    OpenVINO™ Security <documentation/openvino-security>
-   Legacy Features <documentation/legacy-features>
 
 
 This section provides reference documents that guide you through the OpenVINO toolkit workflow, from preparing models, optimizing them, to deploying them in your own deep learning applications.
 
 | :doc:`API Reference doc path <api/api_reference>`
 | A collection of reference articles for OpenVINO C++, C, and Python APIs.
 
-| :doc:`OpenVINO Ecosystem <documentation/openvino-ecosystem>`
+| :doc:`OpenVINO Ecosystem <about-openvino/openvino-ecosystem>`
 | Apart from the core components, OpenVINO offers tools, plugins, and expansions revolving around it, even if not constituting necessary parts of its workflow. This section gives you an overview of what makes up the OpenVINO toolkit.
 
 | :doc:`OpenVINO Extensibility Mechanism <documentation/openvino-extensibility>`

diff --git a/...ut-openvino/compatibility-and-support.rst → ...cumentation/compatibility-and-support.rst b/...ut-openvino/compatibility-and-support.rst → ...cumentation/compatibility-and-support.rst
diff --git a/...ibility-and-support/supported-devices.rst → ...ibility-and-support/supported-devices.rst b/...ibility-and-support/supported-devices.rst → ...ibility-and-support/supported-devices.rst
@@ -13,7 +13,7 @@ deep learning models:
 :doc:`NPU <../../openvino-workflow/running-inference/inference-devices-and-modes/npu-device>`.
 
 | For their usage guides, see :doc:`Devices and Modes <../../openvino-workflow/running-inference/inference-devices-and-modes>`.
-| For a detailed list of devices, see :doc:`System Requirements <../release-notes-openvino/system-requirements>`.
+| For a detailed list of devices, see :doc:`System Requirements <../../about-openvino/release-notes-openvino/system-requirements>`.
 
 
 Beside running inference with a specific device,
@@ -43,7 +43,7 @@ Feature Support and API Coverage
  :doc:`Multi-stream execution <../../openvino-workflow/running-inference/optimize-inference/optimizing-throughput>`                       Yes     Yes        No
  :doc:`Model caching <../../openvino-workflow/running-inference/optimize-inference/optimizing-latency/model-caching-overview>`            Yes     Partial    Yes
  :doc:`Dynamic shapes <../../openvino-workflow/running-inference/dynamic-shapes>`                                                         Yes     Partial    No
- :doc:`Import/Export <../../documentation/openvino-ecosystem>`                                                                            Yes     Yes        Yes
+ :doc:`Import/Export <../../about-openvino/openvino-ecosystem>`                                                                            Yes     Yes        Yes
  :doc:`Preprocessing acceleration <../../openvino-workflow/running-inference/optimize-inference/optimize-preprocessing>`                  Yes     Yes        No
  :doc:`Stateful models <../../openvino-workflow/running-inference/stateful-models>`                                                       Yes     Yes        Yes
  :doc:`Extensibility <../../documentation/openvino-extensibility>`                                                                        Yes     Yes        No

diff --git a/...ity-and-support/supported-models-onnx.rst → ...ity-and-support/supported-models-onnx.rst b/...ity-and-support/supported-models-onnx.rst → ...ity-and-support/supported-models-onnx.rst
diff --git a/...tibility-and-support/supported-models.rst → ...tibility-and-support/supported-models.rst b/...tibility-and-support/supported-models.rst → ...tibility-and-support/supported-models.rst
diff --git a/...lity-and-support/supported-operations.rst → ...lity-and-support/supported-operations.rst b/...lity-and-support/supported-operations.rst → ...lity-and-support/supported-operations.rst
diff --git a/docs/articles_en/documentation/openvino-extensibility.rst b/docs/articles_en/documentation/openvino-extensibility.rst
@@ -25,7 +25,7 @@ OpenVINO Extensibility Mechanism
 
 The Intel® Distribution of OpenVINO™ toolkit supports neural-network models trained with various frameworks, including
 TensorFlow, PyTorch, ONNX, TensorFlow Lite, and PaddlePaddle. The list of supported operations is different for each of the supported frameworks.
-To see the operations supported by your framework, refer to :doc:`Supported Framework Operations <../about-openvino/compatibility-and-support/supported-operations>`.
+To see the operations supported by your framework, refer to :doc:`Supported Framework Operations <../documentation/compatibility-and-support/supported-operations>`.
 
 Custom operations, which are not included in the list, are not recognized by OpenVINO out-of-the-box. The need for custom operation may appear in two cases:
 

diff --git a/docs/articles_en/documentation/openvino-security.rst b/docs/articles_en/documentation/openvino-security.rst
@@ -8,7 +8,7 @@ with encryption or other security tools.
 Actual security and privacy requirements depend on your unique deployment scenario.
 This section provides general guidance on using OpenVINO tools and libraries securely.
 The main security measure for OpenVINO is its
-:doc:`Security Add-on <openvino-ecosystem/openvino-security-add-on>`. You can find its description
+:doc:`Security Add-on <../about-openvino/openvino-ecosystem/openvino-security-add-on>`. You can find its description
 in the Ecosystem section.
 
 .. _encrypted-models:

diff --git a/docs/articles_en/openvino-workflow/model-preparation/convert-model-onnx.rst b/docs/articles_en/openvino-workflow/model-preparation/convert-model-onnx.rst
@@ -62,7 +62,7 @@ Supported ONNX Layers
 #####################
 
 For the list of supported standard layers, refer to the
-:doc:`Supported Operations <../../about-openvino/compatibility-and-support/supported-operations>`
+:doc:`Supported Operations <../../documentation/compatibility-and-support/supported-operations>`
 page.
 
 Additional Resources

diff --git a/docs/articles_en/openvino-workflow/model-preparation/convert-model-paddle.rst b/docs/articles_en/openvino-workflow/model-preparation/convert-model-paddle.rst
@@ -152,7 +152,7 @@ Supported PaddlePaddle Layers
 #############################
 
 For the list of supported standard layers, refer to the
-:doc:`Supported Operations <../../about-openvino/compatibility-and-support/supported-operations>`
+:doc:`Supported Operations <../../documentation/compatibility-and-support/supported-operations>`
 page.
 
 

diff --git a/...ticles_en/openvino-workflow/model-preparation/convert-model-tensorflow-lite.rst b/...ticles_en/openvino-workflow/model-preparation/convert-model-tensorflow-lite.rst
@@ -42,7 +42,7 @@ Supported TensorFlow Lite Layers
 ###################################
 
 For the list of supported standard layers, refer to the
-:doc:`Supported Operations <../../about-openvino/compatibility-and-support/supported-operations>`
+:doc:`Supported Operations <../../documentation/compatibility-and-support/supported-operations>`
 page.
 
 Supported TensorFlow Lite Models

diff --git a/docs/articles_en/openvino-workflow/model-preparation/convert-model-tensorflow.rst b/docs/articles_en/openvino-workflow/model-preparation/convert-model-tensorflow.rst
@@ -383,7 +383,7 @@ Supported TensorFlow and TensorFlow 2 Keras Layers
 ##################################################
 
 For the list of supported standard layers, refer to the
-:doc:`Supported Operations <../../about-openvino/compatibility-and-support/supported-operations>`
+:doc:`Supported Operations <../../documentation/compatibility-and-support/supported-operations>`
 page.
 
 
diff --git a/docs/articles_en/openvino-workflow/model-preparation/setting-input-shapes.rst b/docs/articles_en/openvino-workflow/model-preparation/setting-input-shapes.rst
@@ -22,7 +22,7 @@ To learn more about dynamic shapes in runtime, refer to the
 you can visit `Hugging Face <https://huggingface.co/models>`__.
 
 The OpenVINO Runtime API may present certain limitations in inferring models with undefined
-dimensions on some hardware. See the :doc:`Feature support matrix <../../about-openvino/compatibility-and-support/supported-devices>`
+dimensions on some hardware. See the :doc:`Feature support matrix <../../documentation/compatibility-and-support/supported-devices>`
 for reference. In this case, the ``input`` parameter and the
 :doc:`reshape method <../running-inference/changing-input-shape>` can help to resolve undefined
 dimensions.

diff --git a/docs/articles_en/openvino-workflow/running-inference/dynamic-shapes.rst b/docs/articles_en/openvino-workflow/running-inference/dynamic-shapes.rst
@@ -190,7 +190,7 @@ For the same reason, it is not recommended to leave dimensions as undefined, wit
 
 When specifying bounds, the lower bound is not as important as the upper one. The upper bound allows inference devices to allocate memory for intermediate tensors more precisely. It also allows using a fewer number of tuned kernels for different sizes.
 More precisely, benefits of specifying the lower or upper bound is device dependent.
-Depending on the plugin, specifying the upper bounds can be required. For information about dynamic shapes support on different devices, refer to the :doc:`feature support table <../../about-openvino/compatibility-and-support/supported-devices>`.
+Depending on the plugin, specifying the upper bounds can be required. For information about dynamic shapes support on different devices, refer to the :doc:`feature support table <../../documentation/compatibility-and-support/supported-devices>`.
 
 If the lower and upper bounds for a dimension are known, it is recommended to specify them, even if a plugin can execute a model without the bounds.
 

diff --git a/...-workflow/running-inference/optimize-inference/high-level-performance-hints.rst b/...-workflow/running-inference/optimize-inference/high-level-performance-hints.rst
@@ -8,7 +8,7 @@ High-level Performance Hints
                  an inference device.
 
 
-Even though all :doc:`supported devices <../../../about-openvino/compatibility-and-support/supported-devices>` in OpenVINO™ offer low-level performance settings, utilizing them is not recommended outside of very few cases.
+Even though all :doc:`supported devices <../../../documentation/compatibility-and-support/supported-devices>` in OpenVINO™ offer low-level performance settings, utilizing them is not recommended outside of very few cases.
 The preferred way to configure performance in OpenVINO Runtime is using performance hints. This is a future-proof solution fully compatible with the :doc:`automatic device selection inference mode <../inference-devices-and-modes/auto-device-selection>` and designed with *portability* in mind.
 
 The hints also set the direction of the configuration in the right order. Instead of mapping the application needs to the low-level performance settings, and keeping an associated application logic to configure each possible device separately, the hints express a target scenario with a single config key and let the *device* configure itself in response.
@@ -32,7 +32,7 @@ Performance Hints: How It Works
 
 Internally, every device "translates" the value of the hint to the actual performance settings.
 For example, the ``ov::hint::PerformanceMode::THROUGHPUT`` selects the number of CPU or GPU streams.
-Additionally, the optimal batch size is selected for the GPU and the :doc:`automatic batching <../inference-devices-and-modes/automatic-batching>` is applied whenever possible. To check whether the device supports it, refer to the :doc:`Supported devices <../../../about-openvino/compatibility-and-support/supported-devices>` article.
+Additionally, the optimal batch size is selected for the GPU and the :doc:`automatic batching <../inference-devices-and-modes/automatic-batching>` is applied whenever possible. To check whether the device supports it, refer to the :doc:`Supported devices <../../../documentation/compatibility-and-support/supported-devices>` article.
 
 The resulting (device-specific) settings can be queried back from the instance of the ``ov:Compiled_Model``.
 Be aware that the ``benchmark_app`` outputs the actual settings for the ``THROUGHPUT`` hint. See the example of the output below:

diff --git a/docs/notebooks/auto-device-with-output.rst b/docs/notebooks/auto-device-with-output.rst
@@ -6,7 +6,7 @@ device <https://docs.openvino.ai/2025/openvino-workflow/running-inference/infere
 (or AUTO in short) selects the most suitable device for inference by
 considering the model precision, power efficiency and processing
 capability of the available `compute
-devices <https://docs.openvino.ai/2024/about-openvino/compatibility-and-support/supported-devices.html>`__.
+devices <https://docs.openvino.ai/2025/documentation/compatibility-and-support/supported-devices.html>`__.
 The model precision (such as ``FP32``, ``FP16``, ``INT8``, etc.) is the
 first consideration to filter out the devices that cannot run the
 network efficiently.

diff --git a/docs/sphinx_setup/index.rst b/docs/sphinx_setup/index.rst
@@ -196,5 +196,5 @@ Key Features
    LEARN OPENVINO <learn-openvino>
    HOW TO USE - MAIN WORKFLOW <openvino-workflow>
    HOW TO USE - GENERATIVE AI WORKFLOW <openvino-workflow-generative>
-   DOCUMENTATION <documentation>
+   REFERENCE DOCUMENTATION <documentation>
    ABOUT OPENVINO <about-openvino>