correction of spelling mistakes and references

Author: antonia2702

.python-version

@@ -0,0 +1 @@
+esg_venv

docs/source/01_concepts.rst

@@ -1,7 +1,7 @@
 Concepts
 ========
 
-This section explains how to apply the ESG framework and gives an overview of the basic technical concepts.  For more in-depth information especially regarding the discussion of the approach, please refer to the published `research article <https://de.overleaf.com/project/6565c3491f8923df81a997ac>`__.
+This section explains how to apply the ESG framework and gives an overview of the basic technical concepts.  For more in-depth information especially regarding the discussion of the approach, please refer to the published `research article <https://doi.org/10.48550/arXiv.2402.15230>`__.
 
 Framework
 ---------

docs/source/02_example_service.rst

@@ -1,6 +1,6 @@
 Example service implementation
 ==============================
-This section demonstrates a simple but fully functional implementation of a photovoltaic (PV) power gerneration forecast service. For more in-depth information about the individual components, please refer to the :doc:`01_concepts` section or the published `research article <https://de.overleaf.com/project/6565c3491f8923df81a997ac>`__.
+This section demonstrates a simple but fully functional implementation of a photovoltaic (PV) power gerneration forecast service. For more in-depth information about the individual components, please refer to the :doc:`01_concepts` section or the published `research article <https://doi.org/10.48550/arXiv.2402.15230>`__.
 
 1. Preparation of the forecast or optimization code
 ---------------------------------------------------
@@ -66,7 +66,7 @@ parameters by invoking the forecasting or optimization code, as well as task sch
 .. literalinclude:: ../examples/basic_example/source/service/worker.py
    :pyobject: fit_parameters_task
 
-The above code can be found in the `api.py <https://github.com/fzi-forschungszentrum-informatik/energy-service-generics/blob/main/docs/examples/basic_example/source/service/worker.py>`__ file.
+The above code can be found in the `worker.py <https://github.com/fzi-forschungszentrum-informatik/energy-service-generics/blob/main/docs/examples/basic_example/source/service/worker.py>`__ file.
 
 4. Customization of the API component
 -------------------------------------
@@ -76,7 +76,7 @@ The implementation of the API component is available ready-to-use in the ESG fra
    :language: python
    :start-at: api =
 
-The above code can be found in the `worker.py <https://github.com/fzi-forschungszentrum-informatik/energy-service-generics/blob/main/docs/examples/basic_example/source/service/api.py>`__ file.
+The above code can be found in the `api.py <https://github.com/fzi-forschungszentrum-informatik/energy-service-generics/blob/main/docs/examples/basic_example/source/service/api.py>`__ file.
 
 5. Building docker images to derive functional services
 -------------------------------------------------------

docs/source/03_example_client.rst

@@ -4,7 +4,7 @@ This section showcases two example client implementations for the basic example
 
 Minimal client implementation
 ----------------------------------------------
-This minimal client implementation is to be executed on the same machine as the service. The service should be reachable via a localhost port. The client is implemented using a simple UNIX shell script and requires the additional packages **curl** and **jq**. The script below can be used to simulate a client that requests a photovoltaic power generation forecast from the basic example service. Note that this interaction with the `/fit-parameters/` endpoint is omitted in this example but would follow the same structure.
+This minimal client implementation is to be executed on the same machine as the service. The service should be reachable via a localhost port. The client is implemented using a simple UNIX shell script and requires the additional packages **curl** and **jq**. The script below can be used to simulate a client that requests a photovoltaic power generation forecast from the basic example service. Note that this interaction with the ``/fit-parameters/`` endpoint is omitted in this example but would follow the same structure.
 
 .. literalinclude:: ../examples/minimial_client/source/client/main.sh
     :language: bash
@@ -18,6 +18,6 @@ The service integration in a production EMS will probably require a more sophist
     :language: python
     :start-at: import
 
-It is recommended that the client developer specifies the data models themself in order to document the data structure of the downstream application, i.e. the EMS.  This should reduce tedious debugging deep within the downstream application and produce the error right inside the client code. However, it is possible to fetch the data models autommatically from the service.
+It is recommended that the client developer specifies the data models themself in order to document the data structure of the downstream application, i.e. the EMS.  This should reduce tedious debugging deep within the downstream application and produce the error right inside the client code. However, it is possible to fetch the data models automatically from the service.
 
 It is to be noted, that the generic client provided by the ESG package can only be used in a python environment. Nevertheless, if the client code needs to be in a different language it should be possible to implement the logic rather quickly.  `Swagger Codegen <https://swagger.io/tools/swagger-codegen/>`__ can help to partially automate the generation of the client program.