Updates to wK Docs (#5995)

* updates to the docs

* more documentation updates

* updates to docs

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* more docs

* more docs

* more docs

* WIP sharing

* updated datasets

* updated datasets docs

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* restored typechange for changelog

* docs/CHANGELOG.released.md

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docs/automated_analysis.md

@@ -0,0 +1,28 @@
+# Automated Analysis
+
+While webKnossos is great for manual annotation, some datasets are either too big to do by hand or you need results quicker. webKnossos contains early access to automated analysis using machine learning classifiers for dataset segmentations. The webKnossos developer team has many years of experience with training ML models for large-scale data analysis outside of webKnossos. We aim to bring some of this know-how directly into webKnossos itself.
+
+The automated analysis features are designed to provide a general solution to a wide range of (EM) datasets. Since datasets differ in staining protocols, imaging modalities, imaging resolution & fidelity, your results may vary. [Please contact us](mailto:[email protected]) for customized, fine-tuned solutions for your dataset. 
+
+We plan to add more automated analysis features in the future. If you want to work with us on an automated analysis project, [please contact us](mailto:[email protected]). 
+We would love to integrate analysis solutions for more modalities and use cases.
+
+Automated analysis is only available on [webKnossos.org](https://webknossos.org) at the moment. 
+If you want to set up on-premise automated analysis at your institute/workplace, then [please contact us](mailto:[email protected]). 
+
+## Nuclei Inferral
+As a first trial, webKnossos includes nuclei segmentation. This analysis is designed to work with serial block-face electron microscopy (SBEM) data of neural tissue (brain/cortex) and will find and segment all nuclei within the dataset.
+
+You can launch the nuclei inferral from the `Info` tab in the right-hand side panel. Use the `Process Dataset` link to start the analysis.
+
+Computation time for this analysis depends directly on the size of your dataset. 
+Expect a few hours for medium-sized volumetric EM datasets. 
+The finished analysis will be available as a new dataset from your dashboard. You can monitor the status and progress of the analysis job from the `Processing Jobs` section of the `Administration` menu at the top of the screen.
+
+/todo add screenshot of nuclei classification
+/todo add screenshot of jobs list
+
+## Custom Analysis
+At the moment, webKnossos can not be used to train a custom classifier itself. This might be something that we add in the future if there is enough interest in this.
+
+If you are interested in specialized, automated analysis, image segmentation, object detection etc. than feel to [contact us](mailto:[email protected]). The webKnossos development teams offers [commercial analysis services for](https://webknossos.org/services/automated-segmentation) that. 

docs/dashboard.md

@@ -1,55 +1,54 @@
 # Dashboard
 
-The Dashboard is the entry point to webKnossos.
-You can manage your datasets, create annotations, resume existing annotations and manage active tasks.
+The Dashboard is your entry point to webKnossos.
+You can manage your datasets, create annotations, resume existing annotations and retrieve tasks distributed to you.
 
 ## My Datasets
 This screen shows all the available and accessible datasets for a user.
-The presentation differs corresponding to the user role.
-Normal users can start or continue annotations and work on tasks.
-[Admins and Team Managers](./users.md#access-rights-roles) also have access to dedicated administration screens and advanced dataset properties.
-
-You can **view** the dataset, or create a new **skeleton** or **volume** annotations from this screen.
-Search for your dataset by using the search bar or by sorting any of the table columns.
+You can *view* a dataset (read-only) or start new annotations from this screen.
+Search for your dataset by using the search bar or sorting any of the table columns.
 Learn more about managing datasets in the [Datasets guide](./datasets.md).
 
+The presentation differs corresponding to your user role.
+Regular users can only start or continue annotations and work on tasks.
+[Admins and Team Managers](./users.md#access-rights-roles) also have access to additional administration actions, access-rights management, and advanced dataset properties for each dataset.
+
 ![Dashboard for Team Managers or Admins](./images/dashboard_datasets.png)
-![Dashboard for Normal Users](./images/dashboard_normal_user.png)
+![Dashboard for Regular Users](./images/dashboard_normal_user.png)
 
 ![Video: Community Dataset Gallery & Navigating Through Data](https://www.youtube.com/watch?v=naPL1jfCdOc)
 
 ## My Tasks
 
 With Tasks, you can coordinate large annotation projects with your users.
-Tasks are small assignments that are automatically distributed to users.
+Tasks are small annotation work assignments that are automatically distributed to users. This is particularly useful when you have several users in your organization that you can distribute the work to, e.g., working students, scientific assistances, outside collaborators, etc.
 
-On the Task screen, users can request new tasks, continue to work on existing tasks, and finish tasks.
-These tasks will be assigned based on the user's experience levels, project priority, and task availability.
+On the Task screen, users can request new tasks, continue to work on existing tasks, and finish tasks. These tasks are assigned based on a user's experience level, project priority, and task availability.
 Read more about the tasks feature in the [Tasks and Projects guide](./tasks.md).
 
 ![Work with Tasks](./images/dashboard_tasks.png)
 
-## My Annotations (Explorative)
-Explorative Annotations are all skeleton or volume annotations that do not belong to a task.
-They are created by starting new annotations from the datasets screen or by uploading [NML files](./data_formats.md#nml).
+## My Annotations
+This screen lists all your annotations (skeleton, volume or both) that you started on a dataset (outside of tasks). Annotations are either created by starting new annotations from the "My Datasets" tab, from the webKnossos data viewer, or by uploading an existing annotation from your computer (see [NML files](./data_formats.md#nml) for skeleton annotations).
 
-In this screen, the annotations can be resumed, archived, and downloaded.
-You can also add custom tags to annotations in order to organize them.
+Annotations can be resumed, archived (like delete, but reversible), and downloaded for offline analysis. 
+You can also add custom tags to annotations to organize and group them. Click on one or multiple of your tags if you want to filter a particular group of annotations. 
+Each annotation can be renamed to reflect its content.
 
 ![Manage and resume Explorative Annotations](./images/dashboard_annotations.png)
 ![View archived Explorative Annotations](./images/dashboard_archive.png)
 
 
 ## Shared Annotations
-This screen shows all skeleton or volume annotations that were shared with one of your teams.
-You can directly view the linked annotations and copy them to your account.
+This screen shows all annotations that were shared by other collaborators of your organization. Only annotations shared through the "Team Sharing" mechanic will be listed provided your user account is part of the respective team. Read more about sharing your own annotations in the [Sharing guide](./sharing.md#annotation-sharing).
 
-Read more about sharing your own annotations in the [Sharing guide](./sharing.md#annotation-sharing).
+You can view the linked annotations (read-only) or copy them to your account for modification.
 
 ![View Shared Annotations](./images/shared_annotations_tab.png)
 
 ## Featured Publications
 
-This screen is the same gallery that is used on the public webKnossos screen.
-Here, it also includes non-public datasets.
-See a [live Dataset Gallery](https://demo.webknossos.org).
+This screen lists a number of featured public community datasets and their respective publications hosted by the webKnossos team. Feel free to explore these datasets or to build upon them.
+
+[Contact us](mailto:[email protected]) if you would like your data and publication to be featured here as well.
+