Create subpages and ToC

docs/user_guide.rst

@@ -49,4 +49,4 @@ the RegionProcessor and validated using DataStructureDefinition.
   user_guide/model-registration
   user_guide/config
   user_guide/local-usage
-  user_guide/data-validation
+  user_guide/validation

docs/user_guide/validation.rst

@@ -0,0 +1,17 @@
+.. _validation:
+
+.. currentmodule:: nomenclature
+
+Data validation
+===============
+
+The **nomenclature** package allows users to validate IAMC data in several ways.
+
+For this, validation requirements and criteria can be specified in YAML configuration
+files.
+
+.. toctree::
+  :maxdepth: 1
+
+  validation/data-validation
+  validation/required-data-validation

docs/user_guide/data-validation.rst → docs/user_guide/validation/data-validation.rst

@@ -5,40 +5,6 @@
 Data validation
 ===============
 
-The **nomenclature** package allows users to validate IAMC data in several ways.
-
-For this, validation requirements and criteria can be specified in YAML configuration
-files.
-
-Required data validation
-------------------------
-
-**Required data validation** checks if certain models, variables, regions and/or 
-periods of time are covered in the datapoints.
-
-For this, a configuration file specifies the model(s) and dimension(s) expected
-in the dataset. These are ``variable``, ``region`` and/or ``year``.
-Alternatively, instead of using ``variable``, it is possible to declare measurands,
-which jointly specify variables and units.
-
-.. code:: yaml
-
-  description: Required variables for running MAGICC
-  model: model_a
-  required_data:
-    - measurand:
-        Emissions|CO2:
-          unit: Mt CO2/yr
-      region: World
-      year: [2020, 2030, 2040, 2050]
-
-In the example above, for *model_a*, the dataset must include datapoints of the
-variable *Emissions|CO2* (measured in *Mt CO2/yr*), in the region *World*, for the
-years 2020, 2030, 2040 and 2050.
-
-Data validation
----------------
-
 **Data validation** checks if data values are within specified ranges.
 
 Consider the example below:
@@ -87,15 +53,12 @@ a separate criteria item) and slower to process.
 Standard usage
 --------------
 
-Run the following in a Python script to check that an IAMC dataset has valid
-(required) data.
+Run the following in a Python script to check that an IAMC dataset has valid data.
 
 .. code-block:: python
 
-  from nomenclature import RequiredDataValidator
   from nomenclature.processor import DataValidator
 
   # ...setting directory/file paths and loading dataset
 
-  RequiredDataValidator.from_file(req_data_yaml).apply(df)
   DataValidator.from_file(data_val_yaml).apply(df)

docs/user_guide/validation/required-data-validation.rst

@@ -0,0 +1,43 @@
+.. _required-data-validation:
+
+.. currentmodule:: nomenclature
+
+Required data validation
+========================
+
+**Required data validation** checks if certain models, variables, regions and/or 
+periods of time are covered in the datapoints.
+
+For this, a configuration file specifies the model(s) and dimension(s) expected
+in the dataset. These are ``variable``, ``region`` and/or ``year``.
+Alternatively, instead of using ``variable``, it is possible to declare measurands,
+which jointly specify variables and units.
+
+.. code:: yaml
+
+  description: Required variables for running MAGICC
+  model: model_a
+  required_data:
+    - measurand:
+        Emissions|CO2:
+          unit: Mt CO2/yr
+      region: World
+      year: [2020, 2030, 2040, 2050]
+
+In the example above, for *model_a*, the dataset must include datapoints of the
+variable *Emissions|CO2* (measured in *Mt CO2/yr*), in the region *World*, for the
+years 2020, 2030, 2040 and 2050.
+
+Standard usage
+--------------
+
+Run the following in a Python script to check that an IAMC dataset has valid
+required data.
+
+.. code-block:: python
+
+  from nomenclature import RequiredDataValidator
+
+  # ...setting directory/file paths and loading dataset
+
+  RequiredDataValidator.from_file(req_data_yaml).apply(df)