diff --git a/docker/ellips/example/Ellipsometry workflow example.ipynb b/docker/ellips/example/Ellipsometry workflow example.ipynb
index 10265d436bac7d0bac5d724e7501670ad419e2c5..d2b57f121992ec350ef9a1299f578fd5053af382 100644
--- a/docker/ellips/example/Ellipsometry workflow example.ipynb	
+++ b/docker/ellips/example/Ellipsometry workflow example.ipynb	
@@ -24,16 +24,24 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "vscode": {
+     "languageId": "python"
+    }
+   },
    "outputs": [],
    "source": [
-    "from nexusparser.tools.dataconverter.convert import convert"
+    "from nexusutils.dataconverter.convert import convert"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "vscode": {
+     "languageId": "python"
+    }
+   },
    "outputs": [],
    "source": [
     "convert(input_file=[\"eln_data.yaml\"],\n",
@@ -54,7 +62,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "vscode": {
+     "languageId": "python"
+    }
+   },
    "outputs": [],
    "source": [
     "from jupyterlab_h5web import H5Web"
@@ -63,7 +75,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "vscode": {
+     "languageId": "python"
+    }
+   },
    "outputs": [],
    "source": [
     "H5Web('SiO2onSi.ellips.nxs')"
@@ -89,7 +105,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "vscode": {
+     "languageId": "python"
+    }
+   },
    "outputs": [],
    "source": [
     "import elli\n",
@@ -111,7 +131,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "vscode": {
+     "languageId": "python"
+    }
+   },
    "outputs": [],
    "source": [
     "ANGLE = 70\n",
@@ -131,7 +155,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "vscode": {
+     "languageId": "python"
+    }
+   },
    "outputs": [],
    "source": [
     "params = ParamsHist()\n",
@@ -166,7 +194,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "vscode": {
+     "languageId": "python"
+    }
+   },
    "outputs": [],
    "source": [
     "@fit(psi_delta, params, ANGLE)\n",
@@ -208,7 +240,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "vscode": {
+     "languageId": "python"
+    }
+   },
    "outputs": [],
    "source": [
     "params"
@@ -227,7 +263,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "vscode": {
+     "languageId": "python"
+    }
+   },
    "outputs": [],
    "source": [
     "fit_stats = model.fit()\n",
@@ -248,7 +288,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "vscode": {
+     "languageId": "python"
+    }
+   },
    "outputs": [],
    "source": [
     "fitted_model = elli.Cauchy(\n",
@@ -273,7 +317,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "vscode": {
+     "languageId": "python"
+    }
+   },
    "outputs": [],
    "source": [
     "fitted_model.get_refractive_index_df().plot(backend='plotly')"
@@ -289,7 +337,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "vscode": {
+     "languageId": "python"
+    }
+   },
    "outputs": [],
    "source": [
     "fitted_model.get_dielectric_df().to_csv('SiO2_diel_func.csv')"
@@ -305,7 +357,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "vscode": {
+     "languageId": "python"
+    }
+   },
    "outputs": [],
    "source": [
     "fit_stats.params['SiO2_n0'].value"
@@ -321,7 +377,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "vscode": {
+     "languageId": "python"
+    }
+   },
    "outputs": [],
    "source": [
     "fit_stats.params"
@@ -338,7 +398,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "vscode": {
+     "languageId": "python"
+    }
+   },
    "outputs": [],
    "source": [
     "fit_stats.chisqr"
@@ -354,7 +418,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "vscode": {
+     "languageId": "python"
+    }
+   },
    "outputs": [],
    "source": [
     "fit_stats"
@@ -363,28 +431,20 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "vscode": {
+     "languageId": "python"
+    }
+   },
    "outputs": [],
    "source": []
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "elli",
+   "display_name": "nxs-parser",
    "language": "python",
-   "name": "elli"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.9.13"
+   "name": "nxs-parser"
   },
   "vscode": {
    "interpreter": {
diff --git a/docker/ellips/example/README.md b/docker/ellips/example/README.md
index 25572e54e9f66412d8fbd6299a4086a730bc603b..3555e9b5c8a88fa8843baf0c85f174a63f2df3b9 100644
--- a/docker/ellips/example/README.md
+++ b/docker/ellips/example/README.md
@@ -7,7 +7,7 @@ This example presents the capabilities of the NOMAD platform to store and standa
 Below, you find an overview of your uploaded data.
 Click on the `> /` button to get a list of your data or select **FILES** from the top menu of this upload.
 You may add your own files to the upload or experiment with the pre-existing electronic lab notebook (ELN) example.
-The ELN follows the general structure of NOMAD ELN templates and you may refer to the [documentation](https://nomad-lab.eu/prod/v1/staging/docs/archive.html)  or a [YouTube tutorial](https://youtu.be/o5ETHmGmnaI) (~1h)
+The ELN follows the general structure of NOMAD ELN templates and you may refer to the [documentation](https://nomad-lab.eu/prod/v1/staging/docs/archive.html) or a [YouTube tutorial](https://youtu.be/o5ETHmGmnaI) (~1h)
 for further information.
 When the ELN is saved a NeXus file will be generated from the provided example data.
 You may also view your supplied or generated NeXus files here with the H5Web viewer.
@@ -21,7 +21,8 @@ To do so open the **FILES** tab and just select a `.nxs` file.
 - NeXus file: SiO2onSi.ellips.nxs (will be created when running the notebook)
 
 # Analyzing the data
-The examples work through the use of NOMAD remote tools hub (NORTH) containers, i.e. besides using and dealing with the uploaded ellipsometry data, an analysis container can be started. If you want to execute the examples locally you may also use your local python and jupyterlab installation. Please refer to the documentation of the [nexusparser](https://github.com/nomad-coe/nomad-parser-nexus), analysis tool [pyElli](https://github.com/PyEllips/pyElli) and [h5web](https://github.com/nomad-coe/nomad-parser-nexus) on how to install it on your machine.
+
+The examples work through the use of NOMAD remote tools hub (NORTH) containers, i.e. besides using and dealing with the uploaded ellipsometry data, an analysis container can be started. If you want to execute the examples locally you may also use your local python and jupyterlab installation. Please refer to the documentation of [nexusutils](https://github.com/nomad-coe/nomad-parser-nexus), analysis tool [pyElli](https://github.com/PyEllips/pyElli) and [h5web](https://github.com/nomad-coe/nomad-parser-nexus) on how to install it on your machine.
 
 To start an analysis, note your upload id (which you find on top of this explanation) and select **ANALYZE** from the top menu, then **NOMAD Remote Tools Hub**.
 In the appearing list you'll find the `ellips` container, click on it and click **LAUNCH**.
diff --git a/docker/mpes/example/E1 Convert to NeXus.ipynb b/docker/mpes/example/E1 Convert to NeXus.ipynb
index 0dee4a7b6e88b3233d21882f6f9922efced7a0b9..4e966a685462b845f8ab84e88c3f7070f54cf85e 100644
--- a/docker/mpes/example/E1 Convert to NeXus.ipynb	
+++ b/docker/mpes/example/E1 Convert to NeXus.ipynb	
@@ -34,11 +34,12 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## Convert the file to NeXus\n",
-    "To convert the available files to the NeXus format we use the convert function readily supplied by the nexusparser.\n",
+    "To convert the available files to the NeXus format we use the convert function readily supplied by nexusutils.\n",
     "It uses the downloaded measurement file, a json config file and an electronic lab notebook (ELN) yaml file.\n",
     "The json config file maps specific metadata from the h5 measurement file to the nxs file, i.e. a pressure reading which automatically gets collected during measurement.\n",
     "The ELN is a file which supplies additional metadata which is written into the NeXus file.\n",
@@ -63,16 +64,17 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from nexusparser.tools.dataconverter.convert import convert"
+    "from nexusutils.dataconverter.convert import convert"
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "The input parameters are defined as follows:\n",
     "\n",
-    "**reader**: The specific reader which gets called inside the nexusparser. This is supplied in the nexusparser python code. If you create a specific reader for your measurement file it gets selecetd here. If you use the binning procedure from FHI to generate a xarray h5 file you should use the reader called `mpes`.\n",
+    "**reader**: The specific reader which gets called inside nexusutils. This is supplied in the nexusutils python code. If you create a specific reader for your measurement file it gets selecetd here. If you use the binning procedure from FHI to generate a xarray h5 file you should use the reader called `mpes`.\n",
     "\n",
     "**nxdl**: The specific nxdl file which to use. For MPES this should always be `NXmpes` or one of its subdefinitions of the form `NXmpes_<name>`.\n",
     "    \n",
@@ -138,7 +140,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.4"
+   "version": "3.10.4 (main, Jul 28 2022, 10:22:15) [Clang 13.1.6 (clang-1316.0.21.2.5)]"
   },
   "vscode": {
    "interpreter": {
diff --git a/docker/mpes/example/E2 Binning of WSe2.ipynb b/docker/mpes/example/E2 Binning of WSe2.ipynb
index c98cb8e87c1eb7d3295374fc98c8c7586c7d4c1c..af4c40deec7138b2f32267bc52cac679fa157b59 100644
--- a/docker/mpes/example/E2 Binning of WSe2.ipynb	
+++ b/docker/mpes/example/E2 Binning of WSe2.ipynb	
@@ -681,7 +681,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from nexusparser.tools.dataconverter.convert import convert"
+    "from nexusutils.dataconverter.convert import convert"
    ]
   },
   {
@@ -744,7 +744,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.4"
+   "version": "3.10.4 (main, Jul 28 2022, 10:22:15) [Clang 13.1.6 (clang-1316.0.21.2.5)]"
   },
   "vscode": {
    "interpreter": {
diff --git a/docker/mpes/example/E3 pyARPES analysis.ipynb b/docker/mpes/example/E3 pyARPES analysis.ipynb
index 2fc24d7b2a97b4fe77f0685cc0c13ff9979b9325..531620ac9bc86800779d53b7f09e1001dc8e654d 100644
--- a/docker/mpes/example/E3 pyARPES analysis.ipynb	
+++ b/docker/mpes/example/E3 pyARPES analysis.ipynb	
@@ -222,7 +222,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
@@ -236,7 +236,12 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.4"
+   "version": "3.10.4 (main, Jul 28 2022, 10:22:15) [Clang 13.1.6 (clang-1316.0.21.2.5)]"
+  },
+  "vscode": {
+   "interpreter": {
+    "hash": "c2ecc4d45d4efcd07af778d75fd26bf86d0642a6646ea5c57f06d5857684e419"
+   }
   }
  },
  "nbformat": 4,
diff --git a/docker/nexus/Dockerfile b/docker/nexus/Dockerfile
index be403fbe8fadf3955cae31e36fcd276a28824048..eb003f864f9932cf7c11db966ca5ab89f4e7700b 100644
--- a/docker/nexus/Dockerfile
+++ b/docker/nexus/Dockerfile
@@ -3,15 +3,15 @@ FROM gitlab-registry.mpcdf.mpg.de/nomad-lab/nomad-remote-tools-hub/webtop
 # Stack of major installs
 RUN apt-get update && lsb_release -a && \
     apt-get install -y alien:amd64=8.95 \
-        h5utils:amd64=1.13.1-3build1 \
-        hdf-compass:amd64=0.7~b8-2 \
-        hdf5-tools:amd64=1.10.4+repack-11ubuntu1 \
-        libhdf5-openmpi-dev:amd64=1.10.4+repack-11ubuntu1 \
-        wget:amd64=1.20.3-1ubuntu1 \
-        git:amd64=1:2.25.1-1ubuntu3 \
-        libhdf5-dev:amd64=1.10.4+repack-11ubuntu1 \
-        cmake:amd64=3.16.3-1ubuntu1 \
-        libxml2-dev:amd64=2.9.10+dfsg-5ubuntu0.20.04.3 && \
+    h5utils:amd64=1.13.1-3build1 \
+    hdf-compass:amd64=0.7~b8-2 \
+    hdf5-tools:amd64=1.10.4+repack-11ubuntu1 \
+    libhdf5-openmpi-dev:amd64=1.10.4+repack-11ubuntu1 \
+    wget:amd64=1.20.3-1ubuntu1 \
+    git:amd64=1:2.25.1-1ubuntu3 \
+    libhdf5-dev:amd64=1.10.4+repack-11ubuntu1 \
+    cmake:amd64=3.16.3-1ubuntu1 \
+    libxml2-dev:amd64=2.9.10+dfsg-5ubuntu0.20.04.3 && \
     wget https://support.hdfgroup.org/ftp/HDF5/releases/HDF-JAVA/hdfview-3.1.2/bin/HDFView-3.1.2-centos7_64.tar.gz && \
     tar xfvz HDFView-3.1.2-centos7_64.tar.gz && \
     alien --scripts hdfview-3.1.2-1.x86_64.rpm && \
@@ -23,13 +23,13 @@ RUN apt-get update && lsb_release -a && \
     ln -s /opt/hdfview/bin/HDFView /bin/ && \
     apt-get install pip -y && \
     pip install h5py==3.5.0 \
-        h5glance==0.8 \
-        h5grove==1.1.0 \
-        jupyterlab[full]==3.2.9 \
-        jupyterlab_h5web[full]==6.0.0 \
-        punx==0.2.5 \
-        nexpy==0.14.1 \
-        silx[full]==1.0.0 && \
+    h5glance==0.8 \
+    h5grove==1.1.0 \
+    jupyterlab[full]==3.2.9 \
+    jupyterlab_h5web[full]==6.0.0 \
+    punx==0.2.5 \
+    nexpy==0.14.1 \
+    silx[full]==1.0.0 && \
     jupyter lab build
 
 #nexus definitions
@@ -63,10 +63,10 @@ RUN pip install Flask==1.1.2
 
 #nexus-parser
 RUN pip install --upgrade pip && pip install nomad-lab==1.1.1 \
-        --extra-index-url https://gitlab.mpcdf.mpg.de/api/v4/projects/2187/packages/pypi/simple && \
+    --extra-index-url https://gitlab.mpcdf.mpg.de/api/v4/projects/2187/packages/pypi/simple && \
     git clone https://github.com/nomad-coe/nomad-parser-nexus.git --recursive
 WORKDIR nomad-parser-nexus
 RUN pip install -r requirements.txt && \
     pip install .[all]
 #export NEXUS_DEF_PATH=/definitions/
-#launch checker: python3 /nomad-parser-nexus/nexusparser/tools/read_nexus.py <nexusfile>
+#launch checker: python3 /nomad-parser-nexus/nexusutils/read_nexus.py <nexusfile>