run_udf: Simplified and clarified the schema for data #515 (#519)

* `run_udf`: Simplified and clarified the schema for `data` - no functional change. #515

* Applied proposed changes from code review

Author: m-mohr

CHANGELOG.md

@@ -38,6 +38,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - `filter_spatial`: Clarified that masking is applied using the given geometries. [#469](https://github.com/Open-EO/openeo-processes/issues/469)
 - `load_collection` and `load_stac`: Clarified that scale and offset are not applied automatically when loading the data. [#503](https://github.com/Open-EO/openeo-processes/issues/503)
 - `mod`: Clarified behavior for y = 0
+- `run_udf`: Simplified and clarified the schema for `data` - no functional change.
 - `sqrt`: Clarified that NaN is returned for negative numbers.
 - Clarify allowed `FeatureCollection` geometries in `load_collection`, `mask_polygon`, `apply_polygon`, and `load_stac` [#527](https://github.com/Open-EO/openeo-processes/issues/527)
 

proposals/run_udf_externally.json

@@ -1,7 +1,7 @@
 {
     "id": "run_udf_externally",
     "summary": "Run an externally hosted UDF container",
-    "description": "Runs a compatible UDF container that is either externally hosted by a service provider or running on a local machine of the user. The UDF container must follow the [openEO UDF specification](https://openeo.org/documentation/1.0/udfs.html).\n\nThe referenced UDF service can be executed in several processes such as ``aggregate_spatial()``, ``apply()``, ``apply_dimension()`` and ``reduce_dimension()``. In this case, an array is passed instead of a data cube. The user must ensure that the data is given in a way that the UDF code can make sense of it.",
+    "description": "Runs a compatible UDF container that is either externally hosted by a service provider or running on a local machine of the user. The UDF container must follow the [openEO UDF specification](https://openeo.org/documentation/1.0/udfs.html).\n\nThe referenced UDF service can be executed in several processes such as ``aggregate_spatial()``, ``apply()``, ``apply_dimension()`` and ``reduce_dimension()``. In this case, an array is passed instead of a data cube. The user must ensure that the data is provided in a way that the UDF code can make sense of it.",
     "categories": [
         "cubes",
         "import",
@@ -11,21 +11,10 @@
     "parameters": [
         {
             "name": "data",
-            "description": "The data to be passed to the UDF.",
-            "schema": [
-                {
-                    "title": "Array",
-                    "type": "array",
-                    "minItems": 1,
-                    "items": {
-                        "description": "Any data type."
-                    }
-                },
-                {
-                    "title": "Single Value",
-                    "description": "A single value of any data type."
-                }
-            ]
+            "description": "The data to be passed to the UDF.\n\nUsually, `run_udf` process is used as a child process of a data cube process such as ``reduce_dimension()`` or ``apply()``. These data cube processes define the actual type of this data. For example, in case of ``reduce_dimension()``, `data` will be an array of values, while in case of ``apply()`` it will be a single scalar value.",
+            "schema": {
+                "description": "A value of any data type."
+            }
         },
         {
             "name": "url",

run_udf.json

@@ -1,7 +1,7 @@
 {
     "id": "run_udf",
     "summary": "Run a UDF",
-    "description": "Runs a UDF in one of the supported runtime environments.\n\nThe process can either:\n\n1. load and run a UDF stored in a file on the server-side workspace of the authenticated user. The path to the UDF file must be relative to the root directory of the user's workspace.\n2. fetch and run a remotely stored and published UDF by absolute URI.\n3. run the source code specified inline as string.\n\nThe loaded UDF can be executed in several processes such as ``aggregate_spatial()``, ``apply()``, ``apply_dimension()`` and ``reduce_dimension()``. The user must ensure that the data is given in a way that the UDF code can make sense of it.",
+    "description": "Runs a UDF in one of the supported runtime environments.\n\nThe process can either:\n\n1. load and run a UDF stored in a file on the server-side workspace of the authenticated user. The path to the UDF file must be relative to the root directory of the user's workspace.\n2. fetch and run a remotely stored and published UDF by absolute URI.\n3. run the source code specified inline as string.\n\nThe loaded UDF can be executed in several processes such as ``aggregate_spatial()``, ``apply()``, ``apply_dimension()`` and ``reduce_dimension()``. The user must ensure that the data is provided in a way that the UDF code can make sense of it.",
     "categories": [
         "cubes",
         "import",
@@ -10,21 +10,10 @@
     "parameters": [
         {
             "name": "data",
-            "description": "The data to be passed to the UDF.",
-            "schema": [
-                {
-                    "title": "Array",
-                    "type": "array",
-                    "minItems": 1,
-                    "items": {
-                        "description": "Any data type."
-                    }
-                },
-                {
-                    "title": "Single Value",
-                    "description": "A single value of any data type."
-                }
-            ]
+            "description": "The data to be passed to the UDF.\n\nUsually, `run_udf` process is used as a child process of a data cube process such as ``reduce_dimension()`` or ``apply()``. These data cube processes define the actual type of this data. For example, in case of ``reduce_dimension()``, `data` will be an array of values, while in case of ``apply()`` it will be a single scalar value.",
+            "schema": {
+                "description": "A value of any data type."
+            }
         },
         {
             "name": "udf",