mat3ra · timurbazhirov · Jun 26, 2026 · Jun 26, 2026
diff --git a/.github/workflows/build-tests.yml b/.github/workflows/build-tests.yml
@@ -96,7 +96,7 @@ jobs:
       - name: Checkout actions repository
         uses: actions/checkout@9c091bb21b7c1c1d1991bb908d89e4e9dddfe3e0 # v7.0.0
         with:
-          repository: Exabyte-io/actions
+          repository: mat3ra/actions
           token: ${{ secrets.BOT_GITHUB_TOKEN }}
           path: actions
 

diff --git a/.github/workflows/s3-deploy.yml b/.github/workflows/s3-deploy.yml
@@ -30,7 +30,7 @@ jobs:
           python-version: "3.10"
 
       - name: Build pages (legacy)
-        uses: Exabyte-io/action-mkdocs-build@main
+        uses: mat3ra/action-mkdocs-build@main
 
       - name: Build split sites
         run: |

diff --git a/.gitmodules b/.gitmodules
@@ -1,3 +1,3 @@
 [submodule "esse"]
 	path = data/esse
-	url = https://github.com/Exabyte-io/esse.git
+	url = https://github.com/mat3ra/esse.git
diff --git a/README.md b/README.md
@@ -11,7 +11,7 @@ For a quick installation:
 2. Clone this repository:
 
     ```bash
-    git clone https://github.com/Exabyte-io/documentation.git
+    git clone https://github.com/mat3ra/documentation.git
     ```
 
 3. Setup virtual environment
@@ -457,7 +457,7 @@ Including a clickable image map is done as follows. Note that absolute paths to
 
 Including resolved JSON schemas and associated examples should be done within dedicated `data.md` pages for each concept being explained.
 
-The [markdown_include](https://github.com/Exabyte-io/markdown-include) package is used to include JSON content into markdown documents, by putting direct links to pages inside the [ESSE repository](https://github.com/Exabyte-io/exabyte-esse) instead of copying their contents in the main documentation.
+The [markdown_include](https://github.com/mat3ra/markdown-include) package is used to include JSON content into markdown documents, by putting direct links to pages inside the [ESSE repository](https://github.com/mat3ra/exabyte-esse) instead of copying their contents in the main documentation.
 
 ```text
     === "Schema"

diff --git a/data/example-json/machine-learning-predict.json b/data/example-json/machine-learning-predict.json
@@ -8,7 +8,7 @@
     },
     "owner": {
         "_id": "5b143a4ecd313f405b314224",
-        "slug": "exabyte-io",
+        "slug": "mat3ra",
         "cls": "Account"
     },
     "schemaVersion": "0.2.0",
@@ -219,7 +219,7 @@
                                 "CONTAINER": "production-20160630-cluster-001",
                                 "PROVIDER": "aws",
                                 "REGION": "us-east-1",
-                                "NAME": "/cluster-001-share/groups/exabyte-io/exabyte-io-2021-ml-work/checking-ml-file-property-ec8ToqKwpWDGiyNCS/.job_context/target.pkl"
+                                "NAME": "/cluster-001-share/groups/mat3ra/mat3ra-2021-ml-work/checking-ml-file-property-ec8ToqKwpWDGiyNCS/.job_context/target.pkl"
                             }
                         },
                         {
@@ -230,7 +230,7 @@
                                 "CONTAINER": "production-20160630-cluster-001",
                                 "PROVIDER": "aws",
                                 "REGION": "us-east-1",
-                                "NAME": "/cluster-001-share/groups/exabyte-io/exabyte-io-2021-ml-work/checking-ml-file-property-ec8ToqKwpWDGiyNCS/.job_context/workflow_context_file_mapping"
+                                "NAME": "/cluster-001-share/groups/mat3ra/mat3ra-2021-ml-work/checking-ml-file-property-ec8ToqKwpWDGiyNCS/.job_context/workflow_context_file_mapping"
                             }
                         },
                         {
@@ -241,7 +241,7 @@
                                 "CONTAINER": "production-20160630-cluster-001",
                                 "PROVIDER": "aws",
                                 "REGION": "us-east-1",
-                                "NAME": "/cluster-001-share/groups/exabyte-io/exabyte-io-2021-ml-work/checking-ml-file-property-ec8ToqKwpWDGiyNCS/.job_context/descriptors.pkl"
+                                "NAME": "/cluster-001-share/groups/mat3ra/mat3ra-2021-ml-work/checking-ml-file-property-ec8ToqKwpWDGiyNCS/.job_context/descriptors.pkl"
                             }
                         },
                         {
@@ -252,7 +252,7 @@
                                 "CONTAINER": "production-20160630-cluster-001",
                                 "PROVIDER": "aws",
                                 "REGION": "us-east-1",
-                                "NAME": "/cluster-001-share/groups/exabyte-io/exabyte-io-2021-ml-work/checking-ml-file-property-ec8ToqKwpWDGiyNCS/.job_context/target_scaler.pkl"
+                                "NAME": "/cluster-001-share/groups/mat3ra/mat3ra-2021-ml-work/checking-ml-file-property-ec8ToqKwpWDGiyNCS/.job_context/target_scaler.pkl"
                             }
                         },
                         {
@@ -263,7 +263,7 @@
                                 "CONTAINER": "production-20160630-cluster-001",
                                 "PROVIDER": "aws",
                                 "REGION": "us-east-1",
-                                "NAME": "/cluster-001-share/groups/exabyte-io/exabyte-io-2021-ml-work/checking-ml-file-property-ec8ToqKwpWDGiyNCS/.job_context/descriptor_scaler.pkl"
+                                "NAME": "/cluster-001-share/groups/mat3ra/mat3ra-2021-ml-work/checking-ml-file-property-ec8ToqKwpWDGiyNCS/.job_context/descriptor_scaler.pkl"
                             }
                         },
                         {
@@ -274,7 +274,7 @@
                                 "CONTAINER": "production-20160630-cluster-001",
                                 "PROVIDER": "aws",
                                 "REGION": "us-east-1",
-                                "NAME": "/cluster-001-share/groups/exabyte-io/exabyte-io-2021-ml-work/checking-ml-file-property-ec8ToqKwpWDGiyNCS/.job_context/sklearn_mlp.pkl"
+                                "NAME": "/cluster-001-share/groups/mat3ra/mat3ra-2021-ml-work/checking-ml-file-property-ec8ToqKwpWDGiyNCS/.job_context/sklearn_mlp.pkl"
                             }
                         },
                         {
@@ -285,7 +285,7 @@
                                 "CONTAINER": "production-20160630-cluster-001",
                                 "PROVIDER": "aws",
                                 "REGION": "us-east-1",
-                                "NAME": "/cluster-001-share/groups/exabyte-io/exabyte-io-2021-ml-work/checking-ml-file-property-ec8ToqKwpWDGiyNCS/.job_context/predictions.pkl"
+                                "NAME": "/cluster-001-share/groups/mat3ra/mat3ra-2021-ml-work/checking-ml-file-property-ec8ToqKwpWDGiyNCS/.job_context/predictions.pkl"
                             }
                         },
                         {
@@ -296,7 +296,7 @@
                                 "CONTAINER": "production-20160630-cluster-001",
                                 "PROVIDER": "aws",
                                 "REGION": "us-east-1",
-                                "NAME": "/cluster-001-share/groups/exabyte-io/exabyte-io-2021-ml-work/checking-ml-file-property-ec8ToqKwpWDGiyNCS/.job_context/RMSE.pkl"
+                                "NAME": "/cluster-001-share/groups/mat3ra/mat3ra-2021-ml-work/checking-ml-file-property-ec8ToqKwpWDGiyNCS/.job_context/RMSE.pkl"
                             }
                         }
                     ],

diff --git a/data/example-json/machine-learning-train.json b/data/example-json/machine-learning-train.json
@@ -714,7 +714,7 @@
     "hash": "c0c97c1dffb00371a5aec012306d9b4b",
     "owner": {
         "_id": "5b143a4ecd313f405b314224",
-        "slug": "exabyte-io",
+        "slug": "mat3ra",
         "cls": "Account"
     },
     "creator": {

diff --git a/lang/en/docs/cli/actions/add-software.md b/lang/en/docs/cli/actions/add-software.md
@@ -239,7 +239,7 @@ apptainer exec --nv --bind /export,/cluster-001-share <path-to-image.sif> pw.x -
 To understand the details about library paths, one may inspect modulefiles (e.g.,
 `/cluster-001-share/compute/modulefiles/applications/espresso/7.5-cuda-12.8`)
 available in our clusters and [job scripts](
-https://github.com/Exabyte-io/cli-job-examples/blob/main/espresso/gpu/job.gpu.pbs)
+https://github.com/mat3ra/cli-job-examples/blob/main/espresso/gpu/job.gpu.pbs)
 to see how it is implemented. Do not forget to use a GPU-enabled queue,
 such as [GOF]({{ resources_url }}/infrastructure/clusters/google/) to submit your GPU jobs.
 
@@ -281,7 +281,7 @@ Once the job is completed, all output files will be saved under the directory
 from which the job was submitted. Please follow [this documentation page](
 ../../jobs-cli/batch-scripts/apptainer.md) to find more about Apptainer
 integration. For practical templates, please visit[CLI job examples](
-https://github.com/Exabyte-io/cli-job-examples).
+https://github.com/mat3ra/cli-job-examples).
 
 
 ## Transfer external images

diff --git a/lang/en/docs/data-structured/convention.md b/lang/en/docs/data-structured/convention.md
@@ -1,6 +1,6 @@
 # ESSE Data Convention
 
-Our approach towards storing and organizing structured data is based on the **ESSE Data Convention (EDC)** explained in the present documentation. ESSE stands for Essential Source of Schemas and Examples. The corresponding schema implementations are open-source and available in the [GitHub repository](https://github.com/Exabyte-io/esse) and as a package on [PyPI](https://pypi.org/project/mat3ra-esse/).
+Our approach towards storing and organizing structured data is based on the **ESSE Data Convention (EDC)** explained in the present documentation. ESSE stands for Essential Source of Schemas and Examples. The corresponding schema implementations are open-source and available in the [GitHub repository](https://github.com/mat3ra/esse) and as a package on [PyPI](https://pypi.org/project/mat3ra-esse/).
 
 We use this convention to store and organize the information associated with the [Entities]({{ reference_url }}/entities-general/overview/) present across our platform, and their corresponding [Accounts]({{ reference_url }}/accounts/overview/) and [Permissions]({{ reference_url }}/entities-general/permissions/). The convention is designed with the aim of facilitating both the access and collaboration with regards to such entities. The fundamental practices are further elucidated in the sections below.
 

diff --git a/lang/en/docs/getting-started/content-highlights.md b/lang/en/docs/getting-started/content-highlights.md
@@ -98,15 +98,15 @@ JavaScript packages are available on [npm](https://www.npmjs.com/search?q=%40mat
 
 ### 6.2. Open-Source Repositories
 
-- [Exabyte-io GitHub organization](https://github.com/Exabyte-io/){:target='_blank'} — data structures for materials, workflows, and properties
-- [Materials Designer](https://github.com/Exabyte-io/materials-designer){:target='_blank'} — JavaScript library for web-based materials design
-- [API examples](https://github.com/Exabyte-io/api-examples){:target='_blank'} — Jupyter notebooks demonstrating REST API usage
+- [Mat3ra GitHub organization](https://github.com/mat3ra/){:target='_blank'} — data structures for materials, workflows, and properties
+- [Materials Designer](https://github.com/mat3ra/materials-designer){:target='_blank'} — JavaScript library for web-based materials design
+- [API examples](https://github.com/mat3ra/api-examples){:target='_blank'} — Jupyter notebooks demonstrating REST API usage
 
 ### 6.3. Programmatic Access (REST API)
 
-- [Upload materials](https://github.com/Exabyte-io/api-examples/blob/main/examples/material/create_material.ipynb){:target='_blank'}
-- [Run simulations and extract properties as JSON](https://github.com/Exabyte-io/api-examples/blob/main/examples/job/run-simulations-and-extract-properties.ipynb){:target='_blank'}
-- [All API examples (GitHub)](https://github.com/Exabyte-io/api-examples){:target='_blank'}
+- [Upload materials](https://github.com/mat3ra/api-examples/blob/main/examples/material/create_material.ipynb){:target='_blank'}
+- [Run simulations and extract properties as JSON](https://github.com/mat3ra/api-examples/blob/main/examples/job/run-simulations-and-extract-properties.ipynb){:target='_blank'}
+- [All API examples (GitHub)](https://github.com/mat3ra/api-examples){:target='_blank'}
 
 
 ## 7. Learning Resources

diff --git a/lang/en/docs/index-guide.md b/lang/en/docs/index-guide.md
@@ -165,7 +165,7 @@ Platform access, notebook environments, and software management.
 
 <!--
 TODOs:
-- add noteebooks from https://github.com/Exabyte-io/api-examples/tree/main/other/materials_designer
+- add noteebooks from https://github.com/mat3ra/api-examples/tree/main/other/materials_designer
 - add notebooks for workflows from api-examples
 - add mention of "experiments" from api-examples
 -->
diff --git a/lang/en/docs/infrastructure/clusters/directories.md b/lang/en/docs/infrastructure/clusters/directories.md
@@ -6,7 +6,7 @@ The following directories are present under the home folder of each cluster (ref
 .
 ├── data
 ├── dropbox              => /dropbox/gmogni
-├── exabyte-io           => /cluster-001-share/groups/exabyte-io
+├── mat3ra           => /cluster-001-share/groups/mat3ra
 └── job_script_templates => /export/compute/job_script_templates
 ```
 
@@ -33,9 +33,9 @@ The "dropbox" and "job_script_templates" folders are present under both Cluster
 
 ## Shared Folders for Organizations
 
-Simulations data for [Organizations]({{ reference_url }}/collaboration/organizations/overview/) (collaborative [accounts]({{ reference_url }}/accounts/overview/)) is stored in a dedicated **shared folder** accessible by its **members only**. This shared folder bears the same name as the Organization itself: for example, "exabyte-io" in the visual above.  Simulation files present under this data are organized according to the Project/Job based directory naming explained below.
+Simulations data for [Organizations]({{ reference_url }}/collaboration/organizations/overview/) (collaborative [accounts]({{ reference_url }}/accounts/overview/)) is stored in a dedicated **shared folder** accessible by its **members only**. This shared folder bears the same name as the Organization itself: for example, "mat3ra" in the visual above.  Simulation files present under this data are organized according to the Project/Job based directory naming explained below.
 
-Each organization of which the user is member has its own corresponding shared directory. For example, organization `exabyte-io` has its folder under the path `/share/groups/exabyte-io/`.
+Each organization of which the user is member has its own corresponding shared directory. For example, organization `mat3ra` has its folder under the path `/share/groups/mat3ra/`.
 
 ## Temporary Data
 

diff --git a/lang/en/docs/jupyterlite/accessing-jupyterlite.md b/lang/en/docs/jupyterlite/accessing-jupyterlite.md
@@ -21,7 +21,7 @@ To access JupyterLite directly, navigate to the following URL:
 https://jupyterlite.mat3ra.com/lab/index.html
 ```
 
-To access the Introduction notebook summarizing the functionality available in [mat3ra-made](https://github.com/Exabyte-io/made):
+To access the Introduction notebook summarizing the functionality available in [mat3ra-made](https://github.com/mat3ra/made):
 
 ```
 https://jupyterlite.mat3ra.com/lab/tree?path=made/Introduction.ipynb

diff --git a/lang/en/docs/jupyterlite/dependencies-installation.md b/lang/en/docs/jupyterlite/dependencies-installation.md
@@ -21,7 +21,7 @@ from utils.jupyterlite import get_materials
 ## Listing notebook dependencies in `config.yaml`
 
 Some of the necessary packages are compiled into pure Python wheels and provided inside the `mat3ra-api-examples` package. In top-level `packages` folder.
-The dependencies for each notebook and default ones are listed in the [`config.yml` file]("https://github.com/Exabyte-io/api-examples/blob/5e0109589da981b60fec1c1cfcae1977abbbd8ec/config.yml") on the top-level.
+The dependencies for each notebook and default ones are listed in the [`config.yml` file]("https://github.com/mat3ra/api-examples/blob/5e0109589da981b60fec1c1cfcae1977abbbd8ec/config.yml") on the top-level.
 
 To install packages required for the notebook, one can use `install_packages` function from `utils.jupyterlite` module and provide the name of the notebook and the relative path to the `config.yml` file:
 

diff --git a/lang/en/docs/materials-designer/header-menu/input-output/standata-import.md b/lang/en/docs/materials-designer/header-menu/input-output/standata-import.md
@@ -23,4 +23,4 @@ Materials (Graphene and Ni in this case) should now be available in the material
 
 ## Links
 
-1. Standata repository on <a href="https://github.com/Exabyte-io/standata" target="_blank">GitHub</a>. 
+1. Standata repository on <a href="https://github.com/mat3ra/standata" target="_blank">GitHub</a>. 
diff --git a/lang/en/docs/materials/actions/set-default.md b/lang/en/docs/materials/actions/set-default.md
@@ -4,4 +4,4 @@ The initial default material for a new Exabyte account is set to FCC Silicon [^1
 
 ## Links
 
-[^1]: [Example Si FCC material, Exabyte Platform Website](https://platform.mat3ra.com/exabyte-io/materials/cMK8Z5hZMo23iDb9Z)
+[^1]: [Example Si FCC material, Exabyte Platform Website](https://platform.mat3ra.com/mat3ra/materials/cMK8Z5hZMo23iDb9Z)
diff --git a/lang/en/docs/metadata/general.json b/lang/en/docs/metadata/general.json
@@ -3,7 +3,7 @@
         "chemistry",
         "cloud computing",
         "exabyte",
-        "exabyte-io",
+        "mat3ra",
         "high-performance computing",
         "HPC",
         "industry",

diff --git a/lang/en/docs/properties-directory/non-scalar/workflow.md b/lang/en/docs/properties-directory/non-scalar/workflow.md
@@ -8,7 +8,7 @@ workflow being generated and placed in the user's account.
 ## Creation during ML Jobs
 
 If any unit in the workflow has the `workflow:pyml_predict` property,
-[Express will be called](https://github.com/Exabyte-io/express/blob/dev/express/properties/workflow.py) to construct
+[Express will be called](https://github.com/mat3ra/express/blob/dev/express/properties/workflow.py) to construct
 the new predict workflow. The following process is performed to convert a workflow from "Train" to "Predict" mode:
 
 - The `IS_WORKFLOW_RUNNING_TO_PREDICT` flag is set to `True`

diff --git a/lang/en/docs/properties/data/periodic-table.md b/lang/en/docs/properties/data/periodic-table.md
@@ -6,4 +6,4 @@ We assembled the data using the open-source Ref. [^1] below.
 
 ## Links
 
-[^1]: [Exabyte.io Periodic Table Data, JSON, Github Repository](https://github.com/Exabyte-io/periodic-table)
+[^1]: [Exabyte.io Periodic Table Data, JSON, Github Repository](https://github.com/mat3ra/periodic-table)
diff --git a/lang/en/docs/rest-api/api-client.md b/lang/en/docs/rest-api/api-client.md
@@ -2,14 +2,14 @@
 
 ## Python
 
-We have deployed a python-based [**API client**](https://github.com/Exabyte-io/exabyte-api-client)[^1] providing access to the RESTful-API endpoints. Readers are referred to the source code repository linked below for more information.
+We have deployed a python-based [**API client**](https://github.com/mat3ra/api-client)[^1] providing access to the RESTful-API endpoints. Readers are referred to the source code repository linked below for more information.
 
 ## Other
 
 Please [contact us]({{ interface_url }}/ui/support/) if you are interested in any other programming languages. We are able to produce one shortly.
 
 ## Links
 
-[^1]: [Exabyte API Client repository, Github](https://github.com/Exabyte-io/exabyte-api-client)
+[^1]: [Mat3ra API Client repository, Github](https://github.com/mat3ra/api-client)
 
 ///FOOTNOTES GO HERE///
diff --git a/lang/en/docs/rest-api/api-examples.md b/lang/en/docs/rest-api/api-examples.md
@@ -2,10 +2,10 @@
 
 We published an open-source repository[^1] with examples for performing some of the most common tasks in the Mat3ra.com platform through the API in Jupyter Notebook format. Readers are referred to the original online link below for more information.
 
-Rendered notebooks are available in the [API Examples repository](https://github.com/Exabyte-io/exabyte-api-examples).
+Rendered notebooks are available in the [API Examples repository](https://github.com/mat3ra/api-examples).
 
 ## Links
 
-[^1]: [Exabyte API Examples repository, GitHub](https://github.com/Exabyte-io/exabyte-api-examples)
+[^1]: [Mat3ra API Examples repository, GitHub](https://github.com/mat3ra/api-examples)
 
 ///FOOTNOTES GO HERE///
diff --git a/lang/en/docs/software-directory/scripting/jupyter-lab/data.md b/lang/en/docs/software-directory/scripting/jupyter-lab/data.md
@@ -18,8 +18,8 @@ We present in what follows the [structured representation]({{ data_url }}/data-s
 
 1. Initially, the root of the Dropbox folder is passed to the application on the start, so the files at the root of the [Dropbox]({{ resources_url }}/data-in-objectstorage/dropbox/) directory can be accessed
 2. Upon each "Save and Checkpoint" action invoked inside the notebook, the ipynb file is overwritten. A new version is stored in the file system, and a checkpoint is saved to the job inside its directory both in the [command-line]({{ cli_url }}/jobs-cli/batch-scripts/directories/#working-directory) and on the [web interface]({{ resources_url }}/data-in-objectstorage/files/).
-3. All notebooks have access to the filesystem accessible to the user on the corresponding computational node, namely the [home]({{ resources_url }}/infrastructure/clusters/directories/) and [share]({{ resources_url }}/infrastructure/clusters/directories/) directories. For example, the following command will list the shared directory for the account "exabyte-io", when invoked inside the Jupyter Notebook running on "cluster-007":
+3. All notebooks have access to the filesystem accessible to the user on the corresponding computational node, namely the [home]({{ resources_url }}/infrastructure/clusters/directories/) and [share]({{ resources_url }}/infrastructure/clusters/directories/) directories. For example, the following command will list the shared directory for the account "mat3ra", when invoked inside the Jupyter Notebook running on "cluster-007":
 
     ```bash
-    ls -lhta /cluster-007-share/groups/exabyte-io
+    ls -lhta /cluster-007-share/groups/mat3ra
     ```
Original file line number	Diff line number	Diff line change
Expand Up		@@ -23,4 +23,4 @@ Materials (Graphene and Ni in this case) should now be available in the material

		## Links

		1. Standata repository on <a href="https://github.com/Exabyte-io/standata" target="_blank">GitHub</a>.
		1. Standata repository on <a href="https://github.com/mat3ra/standata" target="_blank">GitHub</a>.
Original file line number	Diff line number	Diff line change
Expand Up		@@ -4,4 +4,4 @@ The initial default material for a new Exabyte account is set to FCC Silicon [^1

		## Links

		[^1]: [Example Si FCC material, Exabyte Platform Website](https://platform.mat3ra.com/exabyte-io/materials/cMK8Z5hZMo23iDb9Z)
		[^1]: [Example Si FCC material, Exabyte Platform Website](https://platform.mat3ra.com/mat3ra/materials/cMK8Z5hZMo23iDb9Z)
Original file line number	Diff line number	Diff line change
Expand Up		@@ -6,4 +6,4 @@ We assembled the data using the open-source Ref. [^1] below.

		## Links

		[^1]: [Exabyte.io Periodic Table Data, JSON, Github Repository](https://github.com/Exabyte-io/periodic-table)
		[^1]: [Exabyte.io Periodic Table Data, JSON, Github Repository](https://github.com/mat3ra/periodic-table)