shorten meta descriptions

docs/aggregators.rst

@@ -116,5 +116,5 @@ This extension can then simply be called as such:
 
 .. meta::
    :description lang=en:
-      Aggregators are responsible for combining client model updates into a combiner-level global model. During a training session, the combiners will instantiate an Aggregator and use it to process the incoming model updates from clients.
+      Aggregators are responsible for combining client model updates into a combiner-level global model.
    :keywords: Federated Learning, Aggregators, Federated Learning Framework, Federated Learning Platform, FEDn, Scaleout Systems

docs/apiclient.rst

@@ -137,6 +137,6 @@ For more information on how to use the APIClient, see the :py:mod:`fedn.network.
 
 .. meta::
    :description lang=en:
-      FEDn comes with an APIClient - a Python3 library that can be used to interact with FEDn programmatically. In this tutorial we show how to use the APIClient to initialize the server-side with the compute package and seed models, run and control training sessions and to retrieve models and metrics.
+      FEDn comes with an APIClient - a Python3 library that can be used to interact with FEDn programmatically.
    :keywords: Federated Learning, APIClient, Federated Learning Framework, Federated Learning Platform, FEDn, Scaleout Systems
 

docs/architecture.rst

@@ -54,6 +54,6 @@ many different possible outcomes can be achieved. Good starting configurations a
 
 .. meta::
    :description lang=en:
-      Architecture overview - Constructing a federated model with FEDn amounts to a) specifying the details of the client-side training code and data integrations, and b) deploying the federated network.
+      Architecture overview - An overview of the FEDn federated learning platform architecture.
    :keywords: Federated Learning, Architecture, Federated Learning Framework, Federated Learning Platform, FEDn, Scaleout Systems
 

docs/developer.rst

@@ -267,6 +267,6 @@ You can use `--token` flags in the FEDn CLI to set the access token.
 
 .. meta::
    :description lang=en:
-      During development on FEDn, and when working on own extentions including aggregators and helpers, it is useful to have a local development setup of the core FEDn server-side services (controller, combiner etc). We provide Dockerfiles and docker-compose template for an all-in-one local sandbox
+      During development on FEDn, and when working on own extentions including aggregators and helpers, it is useful to have a local development setup.
    :keywords: Federated Learning, Developer guide, Federated Learning Framework, Federated Learning Platform, FEDn, Scaleout Systems
 

docs/faq.rst

@@ -89,6 +89,6 @@ with the Scaleout team.
 
 .. meta::
    :description lang=en:
-      How do you approach the question of output privacy? We take security in (federated) machine learning seriously. Federated learning is a foundational technology that improves input privacy in machine learning by allowing datasets to stay local and private, and not copied to a server.
+      How do you approach the question of output privacy? We take security in (federated) machine learning seriously.
    :keywords: Federated Learning, FAQ, Federated Learning Framework, Federated Learning Platform, FEDn, Scaleout Systems
 

docs/helpers.rst

@@ -30,6 +30,6 @@ for further details.
 
 .. meta::
    :description lang=en:
-      Model marshalling - In federated learning, model updates need to be serialized and deserialized in order to be transferred between clients and server/combiner. There is also a need to write and load models to/from disk, for example to transiently store updates during training rounds.
+      In federated learning, model updates need to be serialized and deserialized in order to be transferred between clients and server/combiner.
    :keywords: Federated Learning, Model marshalling, Federated Learning Framework, Federated Learning Platform, FEDn, Scaleout Systems
 

docs/index.rst

@@ -32,6 +32,6 @@ Indices and tables
 
 .. meta::
     :description lang=en:
-        FEDn is a federated learning platform that is secure, scalable and easy-to-use. FEDn supports the full journey from early testing/exploration, through pilot projects, to real-world deployments and integration.
+        FEDn is a federated learning platform that is secure, scalable and easy-to-use.
     :keywords: Federated Learning, Machine Learning, Federated Learning Framework, Federated Learning Platform, FEDn, Scaleout Systems
 

docs/introduction.rst

@@ -84,7 +84,7 @@ For professionals / Enteprise, we offer `Dedicated support <https://www.scaleout
 
 .. meta::
     :description lang=en:
-        Federated learning is a decentralized approach that tackles the issues of centralized machine learning by allowing models to be trained on data distributed across various locations without moving the data.
+        Federated learning (FL) is a decentralized approach to machine learning. Instead of moving the data, FL moves the computation to where the data is.
     :keywords: Federated Learning, Machine Learning, What is federated machine learning, Federated Learning Framework, Federated Learning Platform
     :og:title: What is Federated Learning?
     :og:description: Federated learning is a decentralized approach that tackles the issues of centralized machine learning by allowing models to be trained on data distributed across various locations without moving the data.

docs/modules.rst

@@ -8,6 +8,6 @@ API reference
 
 .. meta::
    :description lang=en:
-      API reference for FEDn, a federated learning platform that is secure, scalable and easy-to-use. FEDn supports the full journey from early testing/exploration, through pilot projects, to real-world deployments and integration.
+      API reference for FEDn, a federated learning platform that is secure, scalable and easy-to-use.
    :keywords: Federated Learning, API reference, Federated Learning Framework, Federated Learning Platform, FEDn, Scaleout Systems
 

docs/projects.rst

@@ -439,6 +439,6 @@ and its integration with popular machine learning frameworks like PyTorch and Te
 
 .. meta::
     :description lang=en:
-        A FEDn project is a convention for packaging/wrapping machine learning code to be used for federated learning with FEDn. At the core, a project is a directory of files, containing your machine learning code, FEDn entry points, and a specification of the runtime environment for the client.
+        A FEDn project is a convention for packaging/wrapping machine learning code to be used for federated learning with FEDn.
     :keywords: Federated Learning, Machine Learning, Federated Learning Framework, Federated Learning Platform, FEDn, Scaleout Systems
 

docs/quickstart.rst

@@ -247,7 +247,7 @@ to learn how to set up an all-in-one development environment using Docker and do
 :ref:`developer-label`
 
 .. meta::
-   :description lang=en: This tutorial is a quickstart guide to FEDn based on a pre-made FEDn Project. It is designed to serve as a starting point for new developers. The first step is to start the server side (aggregator, controller). We do this by setting up a new Project in FEDn Studio.
+   :description lang=en: This tutorial is a quickstart guide to FEDn based on a pre-made FEDn Project. It is designed to serve as a starting point for new developers.
    :keywords: Getting started with Federated Learning, Federated Learning, Federated Learning Framework, Federated Learning Platform
    :og:title: Getting started with FEDn
    :og:description: This tutorial is a quickstart guide to FEDn based on a pre-made FEDn Project. It is designed to serve as a starting point for new developers.