diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 5ef648fea..7f6741380 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -44,7 +44,7 @@ repos:
     files: "^src/"
     pass_filenames: true
     args: ["--config-file", "setup.cfg"]
-    additional_dependencies: [pydantic>=1.8.0, rich>=10.0.0, ruamel.yaml, anyio>=3.0.0, pyzmq>=22.0.3]
+    additional_dependencies: [pydantic>=1.8.0, rich>=10.0.0, ruamel.yaml, anyio>=3.0.0, pyzmq>=22.0.3, bidict]
 
 
 - repo: git://github.com/pre-commit/pre-commit-hooks
diff --git a/dev/dev.ipynb b/dev/dev.ipynb
new file mode 100644
index 000000000..4cc9d869e
--- /dev/null
+++ b/dev/dev.ipynb
@@ -0,0 +1,75 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The autoreload extension is already loaded. To reload it, use:\n",
+      "  %reload_ext autoreload\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": "<IPython.core.display.Image object>"
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%load_ext autoreload\n",
+    "%autoreload 2\n",
+    "\n",
+    "from kiara import Kiara\n",
+    "from rich.jupyter import print\n",
+    "\n",
+    "from kiara.utils.jupyter import graph_to_image, save_image\n",
+    "\n",
+    "kiara: Kiara = Kiara.instance()\n",
+    "\n",
+    "# print(kiara.available_module_types)\n",
+    "\n",
+    "# # print('---')\n",
+    "workflow = kiara.create_workflow(\"language.topic_modeling\")\n",
+    "#\n",
+    "# kiara.explain(workflow.steps)\n",
+    "#\n",
+    "save_image(workflow.structure.data_flow_graph_simple, path=\"/tmp/data_flow.png\")\n",
+    "\n",
+    "graph_to_image(workflow.structure.data_flow_graph_simple)\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/docs/modules/module_development.ipynb b/docs/modules/module_development.ipynb
new file mode 100644
index 000000000..3c623465f
--- /dev/null
+++ b/docs/modules/module_development.ipynb
@@ -0,0 +1,52 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "collapsed": true,
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "# Developing *kiara* modules\n",
+    "\n",
+    "This page will show you how to create your own *kiara* modules. It's early days still, so the way this is done\n",
+    "currently is not as pythonic, user-friendly and easy as I hope it will eventually be. I do hope it is easy enough\n",
+    "for everyone with a bit of Python experience to be able to create their own, simple modules, though.\n",
+    "\n",
+    "## (Optional) Create a project structure\n",
+    "\n",
+    "*kiara* modules live in Python packages. Although technically it would be possible to just use Python files,\n",
+    "this is not supported for now, possibly ever. The main reason for that is that it is very important to be\n",
+    "able to pinpoint the exact version of a module that was used to create/transform some data. Python packages\n",
+    "can be versioned (as well as their dependencies) relatively easy, in a generic way. Simple scripts can't,\n",
+    "at least not to the extend we need.\n",
+    "\n",
+    "Creating Python packages correctly is not trivial, which is why I created a [project template](https://github.com/DHARPA-Project/kiara_modules.project_template) that includes\n",
+    "all the necessary bits and integrations to make this as painless as possible."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/docs/usage.md b/docs/usage.md
index a8f257958..552fe665f 100644
--- a/docs/usage.md
+++ b/docs/usage.md
@@ -23,11 +23,11 @@ Display information about a modules, like description, configuration schema, sou
 
 #### ...for a core module
 
-{{ cli("kiara", "module", "describe-type", "and") }}
+{{ cli("kiara", "module", "explain-type", "and") }}
 
 #### ...for a pipeline module
 
-{{ cli("kiara", "module", "describe-type", "nand") }}
+{{ cli("kiara", "module", "explain-type", "nand") }}
 
 ### get properties of an instantiated module
 
@@ -38,11 +38,11 @@ This command also can take module configuration, in different forms. This will b
 
 #### ...for a core module
 
-{{ cli("kiara", "module", "describe-instance", "and") }}
+{{ cli("kiara", "module", "explain-instance", "and") }}
 
 #### ...for a pipeline module
 
-{{ cli("kiara", "module", "describe-instance", "nand") }}
+{{ cli("kiara", "module", "explain-instance", "nand") }}
 
 ## pipeline-specific sub-commands
 
diff --git a/onboarding.folder_to_table.json b/onboarding.folder_to_table.json
new file mode 100644
index 000000000..5dafaa6f9
--- /dev/null
+++ b/onboarding.folder_to_table.json
@@ -0,0 +1,20 @@
+{
+  "table": {
+    "id": [
+      0,
+      1
+    ],
+    "rel_path": [
+      "csv_1.csv",
+      "csv_2.csv"
+    ],
+    "file_name": [
+      "csv_1.csv",
+      "csv_2.csv"
+    ],
+    "content": [
+      "a,b,c\nd,e,f\n",
+      "a,b,c\nd,e,f\n"
+    ]
+  }
+}
\ No newline at end of file
diff --git a/setup.cfg b/setup.cfg
index dc5589c86..fa80a2e1f 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -25,6 +25,7 @@ packages = find_namespace:
 install_requires =
     anyio>=3.0.0,<4.0.0
     appdirs>=1.4.4,<2.0.0
+    bidict>=0.21.0
     deepdiff>=5.2.0,<6.0.0
     filetype>=1.0.0,<2.0.0
     networkx>=2.5,<3.0
@@ -32,6 +33,7 @@ install_requires =
     pyarrow>=4.0.0,<5.0.0
     pydantic>=1.7.0,<2.0.0
     python-dateutil>=2.8.0
+    python-slugify>=5.0.0
     pyyaml>=5.4.0,<6.0.0
     pyzmq>=22.0.0,<23.0.0
     rich>=9.0.0,<11.0.0
@@ -52,6 +54,7 @@ console_scripts =
     kiara = kiara.interfaces.cli:cli
 kiara.modules =
     pipeline = kiara.pipeline.module:PipelineModule
+    metadata.extract_python_class = kiara.modules.metadata:ExtractPythonClass
 
 [options.extras_require]
 cli =
@@ -210,6 +213,9 @@ ignore_missing_imports = true
 [mypy-filetype]
 ignore_missing_imports = true
 
+[mypy-kiara_modules.*]
+ignore_missing_imports = true
+
 [mypy-IPython.*]
 ignore_missing_imports = true
 
diff --git a/src/kiara/data/registry.py b/src/kiara/data/registry.py
index 8d5c4a938..99b3ef917 100644
--- a/src/kiara/data/registry.py
+++ b/src/kiara/data/registry.py
@@ -362,6 +362,33 @@ def get_value_data(self, item: typing.Union[str, KiaraValue]) -> typing.Any:
 
         return value
 
+    def get_value_metadata(
+        self,
+        value: typing.Union[KiaraValue, str],
+        *metadata_keys: str,
+        also_return_schema: bool = False,
+    ):
+
+        value = self.get_value_item(value)
+        result = {}
+        missing = set()
+        for metadata_key in metadata_keys:
+            if metadata_keys in value.metadata.keys():
+                result[metadata_key] = value.metadata[metadata_key]["metadata"]
+            else:
+                missing.add(metadata_key)
+
+        if not missing:
+            return result
+
+        _md = self._kiara.get_value_metadata(value, metadata_keys=missing)
+        result.update(_md)
+
+        if also_return_schema:
+            return result
+        else:
+            return {k: v["metadata"] for k, v in result.items()}
+
     def get_value_hash(
         self, item: typing.Union[str, KiaraValue]
     ) -> typing.Union[int, ValueHashMarker]:
diff --git a/src/kiara/data/types/__init__.py b/src/kiara/data/types/__init__.py
index 36e3bf3ba..019738bf2 100644
--- a/src/kiara/data/types/__init__.py
+++ b/src/kiara/data/types/__init__.py
@@ -20,18 +20,17 @@
 """
 
 import datetime
-import networkx
-import networkx as nx
-import pyarrow
 import typing
 from dateutil import parser
 from deepdiff import DeepHash
 from enum import Enum
-from networkx import DiGraph
 from rich.console import Console, ConsoleOptions, RenderResult
 
 from kiara.utils import camel_case_to_snake_case
 
+if typing.TYPE_CHECKING:
+    from kiara.data.values import Value
+
 
 class ValueHashMarker(Enum):
 
@@ -93,9 +92,19 @@ def get_type_transformation_configs(
         The name of the transformation is the key of the result dictionary, the configuration is a module configuration
         (dictionary wth 'module_type' and optional 'module_config', 'input_name' and 'output_name' keys).
         """
-        return {
-            "to_string": {"module_type": "strings.pretty_print", "input_name": "item"}
-        }
+        return {"string": {"module_type": "strings.pretty_print", "input_name": "item"}}
+
+    @classmethod
+    def check_value_type(cls, value: "Value") -> typing.Optional["ValueType"]:
+        return cls.check_data_type(value.get_value_data())
+
+    @classmethod
+    def check_data_type(cls, data: typing.Any) -> typing.Optional["ValueType"]:
+        return None
+
+    @classmethod
+    def relevant_python_types(cls) -> typing.Optional[typing.Iterable[typing.Type]]:
+        return None
 
     def __init__(self, **type_config: typing.Any):
 
@@ -349,50 +358,3 @@ def parse_value(self, v: typing.Any) -> typing.Any:
 
     def validate(cls, value: typing.Any):
         assert isinstance(value, datetime.datetime)
-
-
-class TableType(ValueType):
-    def validate(cls, value: typing.Any) -> None:
-        assert isinstance(value, pyarrow.Table)
-
-    def extract_type_metadata(
-        cls, value: typing.Any
-    ) -> typing.Mapping[str, typing.Any]:
-
-        table: pyarrow.Table = value
-        table_schema = {}
-        for name in table.schema.names:
-            field = table.schema.field(name)
-            md = field.metadata
-            if not md:
-                md = {}
-            _type = field.type
-            _d = {"item_type": str(_type), "arrow_type_id": _type.id, "metadata": md}
-            table_schema[name] = _d
-
-        return {
-            "column_names": table.column_names,
-            "schema": table_schema,
-            "rows": table.num_rows,
-            "size_in_bytes": table.nbytes,
-        }
-
-
-class NetworkGraphType(ValueType):
-    def validate(cls, value: typing.Any) -> typing.Any:
-
-        if not isinstance(value, networkx.Graph):
-            raise ValueError(f"Invalid type '{type(value)}' for graph: {value}")
-        return value
-
-    def extract_type_metadata(
-        cls, value: typing.Any
-    ) -> typing.Mapping[str, typing.Any]:
-
-        graph: nx.Graph = value
-        return {
-            "directed": isinstance(value, DiGraph),
-            "number_of_nodes": len(graph.nodes),
-            "number_of_edges": len(graph.edges),
-            "density": nx.density(graph),
-        }
diff --git a/src/kiara/data/types/graphs.py b/src/kiara/data/types/graphs.py
new file mode 100644
index 000000000..3f3fa84c2
--- /dev/null
+++ b/src/kiara/data/types/graphs.py
@@ -0,0 +1,27 @@
+# -*- coding: utf-8 -*-
+import networkx
+import networkx as nx
+import typing
+from networkx import DiGraph
+
+from kiara.data.types import ValueType
+
+
+class NetworkGraphType(ValueType):
+    def validate(cls, value: typing.Any) -> typing.Any:
+
+        if not isinstance(value, networkx.Graph):
+            raise ValueError(f"Invalid type '{type(value)}' for graph: {value}")
+        return value
+
+    def extract_type_metadata(
+        cls, value: typing.Any
+    ) -> typing.Mapping[str, typing.Any]:
+
+        graph: nx.Graph = value
+        return {
+            "directed": isinstance(value, DiGraph),
+            "number_of_nodes": len(graph.nodes),
+            "number_of_edges": len(graph.edges),
+            "density": nx.density(graph),
+        }
diff --git a/src/kiara/data/types/type_mgmt.py b/src/kiara/data/types/type_mgmt.py
new file mode 100644
index 000000000..a6a435722
--- /dev/null
+++ b/src/kiara/data/types/type_mgmt.py
@@ -0,0 +1,244 @@
+# -*- coding: utf-8 -*-
+import typing
+
+from kiara.data import Value
+from kiara.data.types import ValueType
+
+if typing.TYPE_CHECKING:
+    from kiara.kiara import Kiara
+
+
+class TypeMgmt(object):
+    def __init__(self, kiara: "Kiara"):
+
+        self._kiara: Kiara = kiara
+        self._value_types: typing.Optional[
+            typing.Dict[str, typing.Type[ValueType]]
+        ] = None
+        self._value_type_transformations: typing.Dict[
+            str, typing.Dict[str, typing.Any]
+        ] = {}
+        self._registered_python_classes: typing.Dict[typing.Type, typing.List[str]] = None  # type: ignore
+
+    @property
+    def value_types(self) -> typing.Mapping[str, typing.Type[ValueType]]:
+
+        if self._value_types is not None:
+            return self._value_types
+
+        all_value_type_classes = ValueType.__subclasses__()
+        value_type_dict: typing.Dict[str, typing.Type[ValueType]] = {}
+        for cls in all_value_type_classes:
+            type_name = cls.type_name()
+            if type_name in value_type_dict.keys():
+                raise Exception(
+                    f"Can't initiate types: duplicate type name '{type_name}'"
+                )
+            value_type_dict[type_name] = cls
+
+        self._value_types = value_type_dict
+        return self._value_types
+
+    @property
+    def value_type_names(self) -> typing.List[str]:
+        return list(self.value_types.keys())
+
+    @property
+    def registered_python_classes(
+        self,
+    ) -> typing.Mapping[typing.Type, typing.Iterable[str]]:
+
+        if self._registered_python_classes is not None:
+            return self._registered_python_classes
+
+        registered_types = {}
+        for name, v_type in self.value_types.items():
+            rel = v_type.relevant_python_types()
+            if rel:
+                for cls in rel:
+                    registered_types.setdefault(cls, []).append(name)
+
+        self._registered_python_classes = registered_types
+        return self._registered_python_classes
+
+    def determine_type(self, data: typing.Any) -> typing.Optional[ValueType]:
+
+        if isinstance(data, Value):
+            data = data.get_value_data()
+
+        result: typing.List[ValueType] = []
+
+        registered_types = set(self.registered_python_classes.get(data.__class__, []))
+        for cls in data.__class__.__bases__:
+            reg = self.registered_python_classes.get(cls)
+            if reg:
+                registered_types.update(reg)
+
+        if registered_types:
+            for rt in registered_types:
+                _cls: typing.Type[ValueType] = self.get_value_type_cls(rt)
+                match = _cls.check_data_type(data)
+                if match:
+                    result.append(match)
+
+        # TODO: re-run all checks on all modules, not just the ones that registered interest in the class
+
+        if len(result) == 0:
+            return None
+        elif len(result) > 1:
+            result_str = [x.type_name() for x in result]
+            raise Exception(
+                f"Multiple value types found for value: {', '.join(result_str)}."
+            )
+        else:
+            return result[0]
+
+    def get_value_type_cls(self, type_name: str) -> typing.Type[ValueType]:
+
+        t = self.value_types.get(type_name, None)
+        if t is None:
+            raise Exception(
+                f"No value type '{type_name}', available types: {', '.join(self.value_types.keys())}"
+            )
+        return t
+
+    def get_value_type_transformations(
+        self, value_type_name: str
+    ) -> typing.Mapping[str, typing.Mapping[str, typing.Any]]:
+        """Return available transform pipelines for value types."""
+
+        if value_type_name in self._value_type_transformations.keys():
+            return self._value_type_transformations[value_type_name]
+
+        type_cls = self.get_value_type_cls(type_name=value_type_name)
+        _configs = type_cls.get_type_transformation_configs()
+        if _configs is None:
+            configs = {}
+        else:
+            configs = dict(_configs)
+        for base in type_cls.__bases__:
+            if hasattr(base, "get_type_transformation_configs"):
+                _b_configs = base.get_type_transformation_configs()  # type: ignore
+                if not _b_configs:
+                    continue
+                for k, v in _b_configs.items():
+                    if k not in configs.keys():
+                        configs[k] = v
+
+        # TODO: check input type compatibility?
+        result: typing.Dict[str, typing.Dict[str, typing.Any]] = {}
+        for name, config in configs.items():
+            config = dict(config)
+            module_type = config.pop("module_type", None)
+            if not module_type:
+                raise Exception(
+                    f"Can't create transformation '{name}' for type '{value_type_name}', no module type specified in config: {config}"
+                )
+            module_config = config.pop("module_config", {})
+            module = self._kiara.create_module(
+                f"_transform_{value_type_name}_{name}",
+                module_type=module_type,
+                module_config=module_config,
+            )
+
+            if "input_name" not in config.keys():
+
+                if len(module.input_schemas) == 1:
+                    config["input_name"] = next(iter(module.input_schemas.keys()))
+                else:
+                    required_inputs = [
+                        inp
+                        for inp, schema in module.input_schemas.items()
+                        if schema.is_required()
+                    ]
+                    if len(required_inputs) == 1:
+                        config["input_name"] = required_inputs[0]
+                    else:
+                        raise Exception(
+                            f"Can't create transformation '{name}' for type '{value_type_name}': can't determine input name between those options: '{', '.join(required_inputs)}'"
+                        )
+
+            if "output_name" not in config.keys():
+
+                if len(module.input_schemas) == 1:
+                    config["output_name"] = next(iter(module.output_schemas.keys()))
+                else:
+                    required_outputs = [
+                        inp
+                        for inp, schema in module.output_schemas.items()
+                        if schema.is_required()
+                    ]
+                    if len(required_outputs) == 1:
+                        config["output_name"] = required_outputs[0]
+                    else:
+                        raise Exception(
+                            f"Can't create transformation '{name}' for type '{value_type_name}': can't determine output name between those options: '{', '.join(required_outputs)}'"
+                        )
+
+            result[name] = {
+                "module": module,
+                "module_type": module_type,
+                "module_config": module_config,
+                "transformation_config": config,
+            }
+
+        self._value_type_transformations[value_type_name] = result
+        return self._value_type_transformations[value_type_name]
+
+    # def get_available_transformations_for_type(
+    #     self, value_type_name: str
+    # ) -> typing.Iterable[str]:
+    #
+    #     return self.get_value_type_transformations(value_type_name=value_type_name)
+
+    # def transform_value(
+    #     self,
+    #     transformation_alias: str,
+    #     value: Value,
+    #     other_inputs: typing.Optional[typing.Mapping[str, typing.Any]] = None,
+    # ) -> Value:
+    #
+    #     transformations = self.get_value_type_transformations(value.value_schema.type)
+    #
+    #     if transformation_alias not in transformations.keys():
+    #         raise Exception(
+    #             f"Can't transform value of type '{value.value_schema.type}', transformation '{transformation_alias}' not available for this type. Available: {', '.join(transformations.keys())}"
+    #         )
+    #
+    #     config = transformations[transformation_alias]
+    #
+    #     transformation_config = config["transformation_config"]
+    #     input_name = transformation_config["input_name"]
+    #
+    #     module: KiaraModule = config["module"]
+    #
+    #     constants = module.get_config_value("constants")
+    #     inputs = dict(constants)
+    #
+    #     if other_inputs:
+    #
+    #         for k, v in other_inputs.items():
+    #             if k in constants.keys():
+    #                 raise Exception(f"Invalid value '{k}' for 'other_inputs', this is a constant that can't be overwrittern.")
+    #             inputs[k] = v
+    #
+    #     defaults = transformation_config.get("defaults", None)
+    #     if defaults:
+    #         for k, v in defaults.items():
+    #             if k in constants.keys():
+    #                 raise Exception(f"Invalid  default value '{k}', this is a constant that can't be overwrittern.")
+    #             if k not in inputs.keys():
+    #                 inputs[k] = v
+    #
+    #     if input_name in inputs.keys():
+    #         raise Exception(
+    #             f"Invalid value for inputs in transform arguments, can't contain the main input key '{input_name}'."
+    #         )
+    #
+    #     inputs[input_name] = value
+    #
+    #     result = module.run(**inputs)
+    #     output_name = transformation_config["output_name"]
+    #
+    #     result_value = result.get_value_obj(output_name)
+    #     return result_value
diff --git a/src/kiara/data/values.py b/src/kiara/data/values.py
index e5e231558..b923bbeda 100644
--- a/src/kiara/data/values.py
+++ b/src/kiara/data/values.py
@@ -277,17 +277,25 @@ def _create_value_table(self, padding=(0, 1)) -> Table:
 
         return table
 
+    def get_metadata(
+        self, *metadata_keys: str, also_return_schema: bool = False
+    ) -> typing.Mapping[str, typing.Mapping[str, typing.Any]]:
+
+        raise NotImplementedError()
+
     def transform(
         self,
-        transformation_alias: str,
+        target_type: str,
         return_data: bool = True,
-        other_inputs: typing.Optional[typing.Mapping[str, typing.Any]] = None,
-    ) -> typing.Any:
-
-        transformed = self._kiara.transform_value(
-            transformation_alias=transformation_alias,
-            value=self,
-            other_inputs=other_inputs,
+        config: typing.Optional[typing.Mapping[str, typing.Any]] = None,
+        register_result: bool = False,
+    ) -> typing.Union[typing.Mapping[str, typing.Any], "Value"]:
+
+        transformed = self._kiara.transform_data(
+            data=self,
+            target_type=target_type,
+            config=config,
+            register_result=register_result,
         )
         if not return_data:
             return transformed
@@ -394,6 +402,27 @@ def get_value_hash(self) -> typing.Any:
         else:
             return self.value_hash
 
+    def get_metadata(
+        self, *metadata_keys: str, also_return_schema: bool = False
+    ) -> typing.Mapping[str, typing.Mapping[str, typing.Any]]:
+
+        result = {}
+        missing = set()
+        for metadata_key in metadata_keys:
+            if metadata_keys in self.metadata.keys():
+                if also_return_schema:
+                    result[metadata_key] = self.metadata[metadata_key]
+                else:
+                    result[metadata_key] = self.metadata[metadata_key]["metadata"]
+            else:
+                missing.add(metadata_key)
+
+        if not missing:
+            return result
+        _md = self.registry.get_value_metadata(self, *missing)
+        result.update(_md)
+        return result
+
     def __eq__(self, other):
 
         # TODO: compare all attributes if id is equal, just to make sure...
@@ -834,12 +863,13 @@ class ValuesInfo(object):
     def __init__(self, value_set: ValueSet, title: typing.Optional[str] = None):
 
         self._value_set: ValueSet = value_set
+        self._title: typing.Optional[str] = title
 
     def create_value_data_table(
         self,
         show_headers: bool = False,
-        transformer: typing.Optional[str] = None,
-        transformer_config: typing.Optional[typing.Mapping[str, typing.Any]] = None,
+        convert_module_type: typing.Optional[str] = None,
+        convert_config: typing.Optional[typing.Mapping[str, typing.Any]] = None,
     ) -> Table:
 
         table = Table(show_header=show_headers, box=box.SIMPLE)
@@ -851,7 +881,9 @@ def create_value_data_table(
 
             if not value.is_set:
                 if value.item_is_valid():
-                    value_str = "-- not set --"
+                    value_str: typing.Union[
+                        ConsoleRenderable, RichCast, str
+                    ] = "-- not set --"
                 else:
                     value_str = "[red]-- not set --[/red]"
             elif value.is_none:
@@ -860,13 +892,14 @@ def create_value_data_table(
                 else:
                     value_str = "[red]-- no value --[/red]"
             else:
-                if not transformer:
+                if not convert_module_type:
                     value_str = value.get_value_data()
                 else:
-                    value_str = value.transform(
-                        transformer, return_data=True, other_inputs=transformer_config
+                    _value_str = value.transform(
+                        convert_module_type, return_data=True, config=convert_config
                     )
-                if not isinstance(value_str, (ConsoleRenderable, RichCast, str)):
+
+                if not isinstance(_value_str, (ConsoleRenderable, RichCast, str)):
                     value_str = str(value_str)
 
             table.add_row(field_name, value_str)
@@ -1042,6 +1075,9 @@ class StepInputField(ValueField):
     connected_pipeline_input: typing.Optional[str] = Field(
         default=None, description="A potential pipeline input."
     )
+    is_constant: bool = Field(
+        "Whether this input is a constant and can't be changed by the user."
+    )
 
     @root_validator(pre=True)
     def ensure_single_connected_item(cls, values):
@@ -1101,6 +1137,9 @@ class PipelineInputField(ValueField):
         description="The step inputs that are connected to this pipeline input",
         default_factory=list,
     )
+    is_constant: bool = Field(
+        "Whether this input is a constant and can't be changed by the user."
+    )
 
     @property
     def alias(self) -> str:
@@ -1117,6 +1156,23 @@ def alias(self) -> str:
         return generate_step_alias(PIPELINE_PARENT_MARKER, self.value_name)
 
 
+class ValueSetType(ValueType):
+    def validate(cls, value: typing.Any) -> None:
+        assert isinstance(value, ValueSet)
+
+    @classmethod
+    def check_data_type(cls, data: typing.Any) -> typing.Optional[ValueType]:
+
+        if isinstance(data, ValueSet):
+            return ValueSetType()
+        else:
+            return None
+
+    @classmethod
+    def relevant_python_types(cls) -> typing.Optional[typing.Iterable[typing.Type]]:
+        return [ValueSet]
+
+
 Value.update_forward_refs()
 DataValue.update_forward_refs()
 LinkedValue.update_forward_refs()
diff --git a/src/kiara/interfaces/cli/__init__.py b/src/kiara/interfaces/cli/__init__.py
index 4f4b177d1..70a82a50a 100644
--- a/src/kiara/interfaces/cli/__init__.py
+++ b/src/kiara/interfaces/cli/__init__.py
@@ -6,22 +6,21 @@
 import os.path
 import sys
 import typing
+from kiara_modules.core.json import DEFAULT_TO_JSON_CONFIG
+from pathlib import Path
+from rich import box
+from rich.console import Console, RenderGroup
 from rich.panel import Panel
+from rich.syntax import Syntax
 
 from kiara import Kiara
-from kiara.data.values import ValuesInfo
 from kiara.interfaces import get_console
 from kiara.module import KiaraModule, ModuleInfo
 from kiara.pipeline.controller import BatchController
 from kiara.pipeline.module import PipelineModuleInfo
 from kiara.processing.parallel import ThreadPoolProcessor
 from kiara.utils import create_table_from_field_schemas, dict_from_cli_args
-
-# from importlib.metadata import entry_points
-
-
-# from asciinet import graph_to_ascii
-
+from kiara.utils.output import OutputDetails
 
 try:
     import uvloop
@@ -43,7 +42,7 @@ def rich_print(msg: typing.Any = None) -> None:
 
 def _create_module_instance(
     ctx, module_type: str, module_config: typing.Iterable[typing.Any]
-):
+) -> KiaraModule:
     config = dict_from_cli_args(*module_config)
 
     kiara_obj = ctx.obj["kiara"]
@@ -115,10 +114,10 @@ def list_modules(ctx, only_pipeline_modules: bool, only_core_modules: bool):
     kiara_obj.explain(p)
 
 
-@module.command(name="describe-type")
+@module.command(name="explain-type")
 @click.argument("module_type", nargs=1, required=True)
 @click.pass_context
-def describe_module_type(ctx, module_type: str):
+def explain_module_type(ctx, module_type: str):
     """Print details of a (Python) module."""
 
     kiara_obj: Kiara = ctx.obj["kiara"]
@@ -139,14 +138,14 @@ def describe_module_type(ctx, module_type: str):
     rich_print(info)
 
 
-@module.command("describe-instance")
+@module.command("explain-instance")
 @click.argument("module_type", nargs=1)
 @click.argument(
     "module_config",
     nargs=-1,
 )
 @click.pass_context
-def describe_module(ctx, module_type: str, module_config: typing.Iterable[typing.Any]):
+def explain_module(ctx, module_type: str, module_config: typing.Iterable[typing.Any]):
     """Describe a step.
 
     A step, in this context, is basically a an instantiated module class, incl. (optional) config."""
@@ -265,6 +264,23 @@ def explain_steps(ctx, pipeline_type: str):
     kiara_obj.explain(structure.to_details().steps_info)
 
 
+@cli.group(name="type")
+@click.pass_context
+def type_group(ctx):
+    """Information about available modules, and details about them."""
+
+
+@type_group.command(name="list")
+@click.pass_context
+def list_types(ctx):
+
+    kiara_obj: Kiara = ctx.obj["kiara"]
+
+    print()
+    for type_name, type in kiara_obj.value_types.items():
+        rich_print(f"{type_name}: {type}")
+
+
 @cli.command()
 @click.argument("module", nargs=1)
 @click.argument("inputs", nargs=-1, required=False)
@@ -276,40 +292,20 @@ def explain_steps(ctx, pipeline_type: str):
     multiple=True,
 )
 @click.option(
-    "--data-details",
+    "--workflow-details",
     "-d",
-    help="Print details/metadata about input/output data.",
+    help="Display additional workflow details.",
     is_flag=True,
-    default=False,
 )
 @click.option(
-    "--only-output",
-    "-o",
-    help="Only print output data. Overrides all other display options.",
-    is_flag=True,
-    default=False,
+    "--output", "-o", help="The output format and configuration.", multiple=True
 )
 @click.pass_context
-async def run(ctx, module, inputs, module_config, data_details, only_output):
+async def run(ctx, module, inputs, module_config, output, workflow_details):
 
     if module_config:
         raise NotImplementedError()
 
-    display_state = True
-    display_input_values = True
-    display_input_details = False
-    display_output_values = True
-    display_output_details = False
-
-    if data_details:
-        display_input_details = True
-        display_output_details = True
-
-    if only_output:
-        display_state = False
-        display_input_values = False
-        display_input_details = False
-
     kiara_obj: Kiara = ctx.obj["kiara"]
 
     if module in kiara_obj.available_module_types:
@@ -335,8 +331,8 @@ async def run(ctx, module, inputs, module_config, data_details, only_output):
         )
 
         one_required = False
-        for schema in module_obj.input_schemas.values():
-            if schema.is_required():
+        for input_name in module_obj.input_names:
+            if module_obj.input_required(input_name):
                 one_required = True
                 break
 
@@ -350,17 +346,41 @@ async def run(ctx, module, inputs, module_config, data_details, only_output):
                 "No inputs provided, not running the workflow. To run it, provide input following this schema:"
             )
             rich_print(inputs_table)
-            sys.exit(0)
+            sys.exit(1)
+
+    output_details = OutputDetails.from_data(output)
+    if output_details.format != "terminal":
+        pass
+
+    force_overwrite = output_details.config.get("force", False)
+
+    # SUPPORTED_TARGETS = ["terminal", "file"]
+    # if output_details.target not in SUPPORTED_TARGETS:
+    #     print()
+    #     rich_print(f"Invalid output target '{output_details.target}', must be one of: [i]{', '.join(SUPPORTED_TARGETS)}[/i]")
+    #     sys.exit(1)
+
+    target_file: typing.Optional[Path] = None
+    if output_details.target != "terminal":
+        if output_details.target == "file":
+            target_dir = Path.cwd()
+            target_file = target_dir / f"{module_name}.{output_details.format}"
+        else:
+            target_file = Path(
+                os.path.realpath(os.path.expanduser(output_details.target))
+            )
+
+        if target_file.exists() and not force_overwrite:
+            print()
+            print(
+                f"Can't run workflow, the target files already exist, and '--output force=true' not specified: {target_file}"
+            )
+            sys.exit(1)
 
     processor = ThreadPoolProcessor()
     # processor = None
     controller = BatchController(processor=processor)
-
     workflow = kiara_obj.create_workflow(module_name, controller=controller)
-
-    # l = DebugListener()
-    # workflow.pipeline.add_listener(l)
-
     list_keys = []
 
     for name, value in workflow.inputs.items():
@@ -374,49 +394,88 @@ async def run(ctx, module, inputs, module_config, data_details, only_output):
     else:
         workflow.controller.process_pipeline()
 
-    transformer = "to_string"
-    transformer_config = {"max_lines": 6}
+    if workflow_details:
+        kiara_obj.explain(workflow.current_state)
 
-    if display_input_values:
-        vi = ValuesInfo(workflow.inputs)
-        vt = vi.create_value_data_table(
-            show_headers=True,
-            transformer=transformer,
-            transformer_config=transformer_config,
-        )
-        rich_print(Panel(vt, title_align="left", title="Workflow input data"))
-        print()
-
-    if display_input_details:
-        vi = ValuesInfo(workflow.inputs)
-        vt = vi.create_value_info_table(show_headers=True)
-        rich_print(Panel(vt, title_align="left", title="Workflow input details"))
-        print()
-
-    if display_state:
-        state_panel = Panel(
-            workflow.current_state,
-            title="Workflow state",
-            title_align="left",
-            padding=(1, 0, 0, 2),
-        )
-        rich_print(state_panel)
-        print()
-
-    if display_output_details:
-        vi = ValuesInfo(workflow.outputs)
-        vt = vi.create_value_info_table(show_headers=True)
-        rich_print(Panel(vt, title_align="left", title="Workflow output details"))
-        print()
-
-    if display_output_values:
-        vi = ValuesInfo(workflow.outputs)
-        vt = vi.create_value_data_table(
-            show_headers=True,
-            transformer=transformer,
-            transformer_config=transformer_config,
-        )
-        rich_print(Panel(vt, title_align="left", title="Workflow output data"))
+    if output_details.target == "terminal":
+        if output_details.format == "terminal":
+            print()
+            pretty_print = kiara_obj.create_workflow("strings.pretty_print")
+            pretty_print.inputs.set_value("item", workflow.outputs)
+
+            renderables = pretty_print.outputs.get_value_data("renderables")
+            output = Panel(RenderGroup(*renderables), box=box.SIMPLE)
+            rich_print("[b]Output data[/b]")
+            rich_print(output)
+        else:
+
+            format = output_details.format
+            available_formats = kiara_obj.get_convert_target_types(
+                source_type="value_set"
+            )
+            if format not in available_formats:
+                print()
+                print(
+                    f"Can't convert to output format '{format}', this format is not supported. Available formats: {', '.join(available_formats)}."
+                )
+                sys.exit(1)
+
+            config = {}
+            config.update(DEFAULT_TO_JSON_CONFIG)
+
+            transformed = kiara_obj.transform_data(
+                workflow.outputs,
+                source_type="value_set",
+                target_type=format,
+                config=config,
+            )
+            transformed_value = transformed.get_value_data("target_value")
+
+            if format in ["json", "yaml"]:
+                transformed_str = Syntax(
+                    transformed_value, lexer_name=format, background_color="default"
+                )
+                rich_print(transformed_str)
+            else:
+                print(transformed_value)
+
+    else:
+        if output_details.format == "terminal":
+            pretty_print = kiara_obj.create_workflow("strings.pretty_print")
+            pretty_print.inputs.set_value("item", workflow.outputs)
+
+            renderables = pretty_print.outputs.get_value_data("renderables")
+            output = Panel(RenderGroup(*renderables), box=box.SIMPLE)
+            with open(target_file, "wt") as f:
+                console = Console(record=True, file=f)
+                console.print(output)
+        else:
+
+            format = output_details.format
+            available_formats = kiara_obj.get_convert_target_types(
+                source_type="value_set"
+            )
+            if format not in available_formats:
+                print()
+                print(
+                    f"Can't convert to output format '{format}', this format is not supported. Available formats: {', '.join(available_formats)}."
+                )
+                sys.exit(1)
+
+            config = {}
+            config.update(DEFAULT_TO_JSON_CONFIG)
+
+            transformed = kiara_obj.transform_data(
+                workflow.outputs,
+                source_type="value_set",
+                target_type=format,
+                config=config,
+            )
+            transformed_value = transformed.get_value_data("target_value")
+
+            target_file.parent.mkdir(parents=True, exist_ok=True)
+            # TODO: check whether to write text or bytes
+            target_file.write_text(transformed_value)
 
 
 # @cli.command()
@@ -426,60 +485,34 @@ async def run(ctx, module, inputs, module_config, data_details, only_output):
 #
 #     os.environ["DEBUG"] = "true"
 #
-#     # kiara = Kiara.instance()
-#
-#     ctx = Context.instance()
-#
-#     sub = ctx.socket(zmq.SUB)
-#     sub.setsockopt_string(zmq.SUBSCRIBE, "")
-#     sub.connect("tcp://127.0.0.1:5556")
-#     while True:
-#         message = sub.recv()
-#         print("Received request: %s" % message)
-#         # socket.send(b"World")
-#
-#     module_info = kiara.get_module_info("import_local_folder")
-#     # kiara.explain(module_info)
-#
-#     workflow = kiara.create_workflow("import_local_folder")
-#     workflow.inputs.path = (
-#         "/home/markus/projects/dharpa/notebooks/TopicModelling/data_tm_workflow"
-#     )
-#
-#     # kiara.explain(workflow.outputs)
-#     kiara.explain(workflow.outputs.file_bundle)
-#
-
-# @cli.command()
-# @click.pass_context
-# def dev2(ctx):
-#     import os
-#
-#     os.environ["DEBUG"] = "true"
+#     kiara = Kiara.instance()
 #
-#     # kiara = Kiara.instance()
+#     workflow = kiara.create_workflow("onboarding.import_local_folder")
 #
-#     ctx = Context.instance()
+#     extended = {
+#         "steps": [
+#             {
+#                 "module_type": "tabular.create_table_from_text_files",
+#                 "module_config": {
+#                     "columns": ["id", "rel_path", "file_name", "content"]
+#                 },
+#                 "step_id": "create_table_from_files",
+#             }
+#         ],
+#         "input_aliases": {"create_table_from_files__files": "file_bundle"},
+#     }
 #
-#     pub = ctx.socket(zmq.PUB)
-#     pub.connect("tcp://127.0.0.1:5555")
-#     while True:
-#         topic = random.randrange(9999, 10005)
-#         messagedata = random.randrange(1, 215) - 80
-#         print("%d %d" % (topic, messagedata))
-#         pub.send_string("%d %d" % (topic, messagedata))
-#         time.sleep(1)
+#     structure = workflow.structure
+#     new_structure = structure.extend(extended)
 #
-#     module_info = kiara.get_module_info("import_local_folder")
-#     # kiara.explain(module_info)
+#     workflow = kiara.create_workflow("tabular.import_table_from_folder")
+#     workflow.inputs.set_value("path", "/home/markus/projects/dharpa/data/csvs")
 #
-#     workflow = kiara.create_workflow("import_local_folder")
-#     workflow.inputs.path = (
-#         "/home/markus/projects/dharpa/notebooks/TopicModelling/data_tm_workflow"
-#     )
+#     import pp
 #
-#     # kiara.explain(workflow.outputs)
-#     kiara.explain(workflow.outputs.file_bundle)
+#     table = workflow.outputs.get_value_obj("table")
+#     md = table.get_metadata()
+#     pp(md)
 
 
 if __name__ == "__main__":
diff --git a/src/kiara/kiara.py b/src/kiara/kiara.py
index 670a95f8c..3a5a66504 100644
--- a/src/kiara/kiara.py
+++ b/src/kiara/kiara.py
@@ -14,6 +14,7 @@
 from kiara.data import Value
 from kiara.data.registry import DataRegistry
 from kiara.data.types import ValueType
+from kiara.data.types.type_mgmt import TypeMgmt
 from kiara.interfaces import get_console
 from kiara.module_config import KiaraWorkflowConfig, PipelineModuleConfig
 from kiara.module_mgmt import ModuleManager
@@ -22,6 +23,7 @@
 from kiara.pipeline.controller import PipelineController
 from kiara.pipeline.pipeline import Pipeline
 from kiara.processing import Job, ModuleProcessor
+from kiara.profiles import ModuleProfileMgmt
 from kiara.utils import get_auto_workflow_alias, get_data_from_file, is_debug
 from kiara.workflow import KiaraWorkflow
 
@@ -67,6 +69,8 @@ def __init__(self, config: typing.Optional[KiaraConfig] = None):
         self._default_pipeline_mgr = PipelineModuleManager(folders=None)
         self._custom_pipelines_mgr = PipelineModuleManager(folders={})
 
+        self._profile_mgmt = ModuleProfileMgmt(kiara=self)
+
         self.start_zmq_device()
         self.start_log_thread()
 
@@ -91,12 +95,7 @@ def __init__(self, config: typing.Optional[KiaraConfig] = None):
 
         self._modules: typing.Dict[str, ModuleManager] = {}
 
-        self._value_types: typing.Optional[
-            typing.Dict[str, typing.Type[ValueType]]
-        ] = None
-        self._value_type_transformations: typing.Dict[
-            str, typing.Dict[str, typing.Any]
-        ] = {}
+        self._type_mgmt: TypeMgmt = TypeMgmt(self)
 
         self._data_registry: DataRegistry = DataRegistry(self)
 
@@ -152,159 +151,93 @@ def explain(self, item: typing.Any):
 
     @property
     def value_types(self) -> typing.Mapping[str, typing.Type[ValueType]]:
-
-        if self._value_types is not None:
-            return self._value_types
-
-        all_value_type_classes = ValueType.__subclasses__()
-        value_type_dict: typing.Dict[str, typing.Type[ValueType]] = {}
-        for cls in all_value_type_classes:
-            type_name = cls.type_name()
-            if type_name in value_type_dict.keys():
-                raise Exception(
-                    f"Can't initiate types: duplicate type name '{type_name}'"
-                )
-            value_type_dict[type_name] = cls
-
-        self._value_types = value_type_dict
-        return self._value_types
+        return self._type_mgmt.value_types
 
     @property
     def value_type_names(self) -> typing.List[str]:
-        return list(self.value_types.keys())
-
-    def get_value_type_cls(self, type_name: str) -> typing.Type[ValueType]:
+        return self._type_mgmt.value_type_names
 
-        t = self.value_types.get(type_name, None)
-        if t is None:
-            raise Exception(
-                f"No value type '{type_name}', available types: {', '.join(self.value_types.keys())}"
-            )
-        return t
+    def determine_type(self, data: typing.Any) -> typing.Optional[ValueType]:
 
-    def get_value_type_transformations(
-        self, value_type_name: str
-    ) -> typing.Mapping[str, typing.Mapping[str, typing.Any]]:
-        """Return available transform pipelines for value types."""
+        return self._type_mgmt.determine_type(data)
 
-        if value_type_name in self._value_type_transformations.keys():
-            return self._value_type_transformations[value_type_name]
-
-        type_cls = self.get_value_type_cls(type_name=value_type_name)
-        _configs = type_cls.get_type_transformation_configs()
-        if _configs is None:
-            configs = {}
-        else:
-            configs = dict(_configs)
-        for base in type_cls.__bases__:
-            if hasattr(base, "get_type_transformation_configs"):
-                _b_configs = base.get_type_transformation_configs()  # type: ignore
-                if not _b_configs:
-                    continue
-                for k, v in _b_configs.items():
-                    if k not in configs.keys():
-                        configs[k] = v
-
-        # TODO: check input type compatibility?
-        result: typing.Dict[str, typing.Dict[str, typing.Any]] = {}
-        for name, config in configs.items():
-            config = dict(config)
-            module_type = config.pop("module_type", None)
-            if not module_type:
-                raise Exception(
-                    f"Can't create transformation '{name}' for type '{value_type_name}', no module type specified in config: {config}"
-                )
-            module_config = config.pop("module_config", {})
-            module = self.create_module(
-                f"_transform_{value_type_name}_{name}",
-                module_type=module_type,
-                module_config=module_config,
-            )
+    def get_value_metadata(
+        self,
+        value: Value,
+        metadata_keys: typing.Union[None, str, typing.Iterable[str]] = None,
+    ):
 
-            if "input_name" not in config.keys():
+        value_type = value.value_schema.type
+        # TODO: validate type exists
 
-                if len(module.input_schemas) == 1:
-                    config["input_name"] = next(iter(module.input_schemas.keys()))
-                else:
-                    required_inputs = [
-                        inp
-                        for inp, schema in module.input_schemas.items()
-                        if schema.is_required()
-                    ]
-                    if len(required_inputs) == 1:
-                        config["input_name"] = required_inputs[0]
-                    else:
-                        raise Exception(
-                            f"Can't create transformation '{name}' for type '{value_type_name}': can't determine input name between those options: '{', '.join(required_inputs)}'"
-                        )
+        all_profiles_for_type = self._profile_mgmt.extract_metadata_profiles.get(
+            value_type, None
+        )
+        if all_profiles_for_type is None:
+            all_profiles_for_type = {}
 
-            if "output_name" not in config.keys():
+        if not metadata_keys:
+            metadata_keys = all_profiles_for_type.keys()
+        elif isinstance(metadata_keys, str):
+            metadata_keys = [metadata_keys]
 
-                if len(module.input_schemas) == 1:
-                    config["output_name"] = next(iter(module.output_schemas.keys()))
-                else:
-                    required_outputs = [
-                        inp
-                        for inp, schema in module.output_schemas.items()
-                        if schema.is_required()
-                    ]
-                    if len(required_outputs) == 1:
-                        config["output_name"] = required_outputs[0]
-                    else:
-                        raise Exception(
-                            f"Can't create transformation '{name}' for type '{value_type_name}': can't determine output name between those options: '{', '.join(required_outputs)}'"
-                        )
+        result = {}
 
-            result[name] = {
-                "module": module,
-                "module_type": module_type,
-                "module_config": module_config,
-                "transformation_config": config,
-            }
+        for mk in metadata_keys:
+            if not all_profiles_for_type or mk not in all_profiles_for_type:
+                raise Exception(
+                    f"Can't extract metadata profile '{mk}' for type '{value_type}': metadata profile does not exist (for this type, anyway)."
+                )
+            profile = all_profiles_for_type[mk]
+            module = profile.create_module(kiara=self)
+            metadata_result = module.run(value=value)
+            result[mk] = metadata_result.get_all_value_data()
 
-        self._value_type_transformations[value_type_name] = result
-        return self._value_type_transformations[value_type_name]
+        return result
 
-    def get_available_transformations_for_type(
-        self, value_type_name: str
-    ) -> typing.Iterable[str]:
+    def get_value_type_cls(self, type_name: str) -> typing.Type[ValueType]:
 
-        return self.get_value_type_transformations(value_type_name=value_type_name)
+        return self._type_mgmt.get_value_type_cls(type_name=type_name)
 
-    def transform_value(
+    def transform_data(
         self,
-        transformation_alias: str,
-        value: Value,
-        other_inputs: typing.Optional[typing.Mapping[str, typing.Any]] = None,
+        data: typing.Any,
+        target_type: str,
+        source_type: typing.Optional[str] = None,
+        config: typing.Optional[typing.Mapping[str, typing.Any]] = None,
+        register_result: bool = False,
     ) -> Value:
 
-        transformations = self.get_value_type_transformations(value.value_schema.type)
-        if transformation_alias not in transformations.keys():
-            raise Exception(
-                f"Can't transform value of type '{value.value_schema.type}', transformation '{transformation_alias}' not available for this type. Available: {', '.join(transformations.keys())}"
-            )
+        if register_result:
+            raise NotImplementedError()
 
-        config = transformations[transformation_alias]
-        input_name = config["transformation_config"]["input_name"]
+        if not source_type:
+            if isinstance(data, Value):
+                source_type = data.type_name
+            else:
+                _source_type = self._type_mgmt.determine_type(data)
+                if not _source_type:
+                    raise Exception(
+                        f"Can't transform data to '{target_type}': can not determine source type."
+                    )
+                source_type = _source_type.type_name()
 
-        module: KiaraModule = config["module"]
+        module = self._profile_mgmt.get_type_conversion_module(
+            source_type=source_type, target_type=target_type  # type: ignore
+        )
+        from kiara.modules.type_conversion import TypeConversionModule
 
-        if other_inputs is None:
-            inputs = {}
-        else:
-            inputs = dict(other_inputs)
-            if input_name in other_inputs.keys():
-                raise Exception(
-                    f"Invalid value for 'other_inputs' in transform arguments, can't contain the main input key '{input_name}'."
-                )
+        if isinstance(module, TypeConversionModule):
 
-        inputs[input_name] = value
+            result = module.run(source_value=data, config=config)
+            return result.get_value_obj("target_value")
+
+        else:
+            raise NotImplementedError()
 
-        result = module.run(**inputs)
-        output_name = config["transformation_config"]["output_name"]
+    def get_convert_target_types(self, source_type: str) -> typing.Iterable[str]:
 
-        result_value = result.get_value_obj(output_name)
-        return result_value
+        return self._profile_mgmt.type_convert_profiles.get(source_type, [])
 
     def add_module_manager(self, module_manager: ModuleManager):
 
diff --git a/src/kiara/metadata/__init__.py b/src/kiara/metadata/__init__.py
deleted file mode 100644
index e69de29bb..000000000
diff --git a/src/kiara/module.py b/src/kiara/module.py
index 44f7ec648..88a9498de 100644
--- a/src/kiara/module.py
+++ b/src/kiara/module.py
@@ -326,6 +326,19 @@ def config(self) -> KIARA_CONFIG:
         """
         return self._config
 
+    def input_required(self, input_name: str):
+
+        if input_name not in self._input_schemas.keys():
+            raise Exception(f"No input '{input_name}' for module '{self.id}'.")
+
+        if not self._input_schemas[input_name].is_required():
+            return False
+
+        if input_name in self.get_config_value("constants"):
+            return False
+        else:
+            return True
+
     def get_config_value(self, key: str) -> typing.Any:
         """Retrieve the value for a specific configuration option.
 
@@ -370,6 +383,7 @@ def input_schemas(self) -> typing.Mapping[str, ValueSchema]:
 
         result = {}
         for k, v in _input_schemas.items():
+
             if isinstance(v, ValueSchema):
                 result[k] = v
             elif isinstance(v, typing.Mapping):
@@ -380,6 +394,23 @@ def input_schemas(self) -> typing.Mapping[str, ValueSchema]:
                 raise Exception(
                     f"Invalid return type when tryping to create schema for '{self.id}': {type(v)}"
                 )
+            default_value = self.config.defaults.get(k, None)
+            constant_value = self.config.constants.get(k, None)
+
+            # value_to_test = None
+            if default_value is not None and constant_value is not None:
+                raise Exception(
+                    f"Module configuration error. Value '{k}' set in both 'constants' and 'defaults', this is not allowed."
+                )
+            # elif default_value is not None:
+            #     value_to_test = default_value
+            # elif constant_value is not None:
+            #     value_to_test = constant_value
+
+            # TODO: perform validation for constants/defaults
+
+            if default_value is not None:
+                result[k].default = default_value
 
         self._input_schemas = result
 
@@ -478,6 +509,10 @@ def clean_value(v: typing.Any) -> typing.Any:
         for k, v in inputs.items():
             v = clean_value(v)
             if not isinstance(v, Value):
+                if k not in self.input_schemas.keys():
+                    raise Exception(
+                        f"Invalid input name '{k}. Not part of the schema, allowed input names: {', '.join(self.input_names)}"
+                    )
                 schema = self.input_schemas[k]
                 v = NonRegistryValue(
                     _init_value=v,  # type: ignore
@@ -590,8 +625,11 @@ def __rich_console__(
         config_str = json.dumps(config, indent=2)
         c = Syntax(config_str, "json", background_color="default")
         table.add_row("config", c)
+
+        constants = self.config.get("constants")
+
         inputs_table = create_table_from_field_schemas(
-            _show_header=True, **self.input_schemas
+            _show_header=True, _constants=constants, **self.input_schemas
         )
         table.add_row("inputs", inputs_table)
         outputs_table = create_table_from_field_schemas(
diff --git a/src/kiara/module_config.py b/src/kiara/module_config.py
index 40e08ea4d..eec0d3fd8 100644
--- a/src/kiara/module_config.py
+++ b/src/kiara/module_config.py
@@ -21,16 +21,20 @@
 
 def create_step_value_address(
     value_address_config: typing.Union[str, typing.Mapping[str, typing.Any]],
-    field_name: str,
+    default_field_name: str,
 ) -> StepValueAddress:
 
+    if isinstance(value_address_config, StepValueAddress):
+        return value_address_config
+
     sub_value: typing.Optional[typing.Mapping[str, typing.Any]] = None
+
     if isinstance(value_address_config, str):
 
         tokens = value_address_config.split(".")
         if len(tokens) == 1:
             step_id = value_address_config
-            output_name = field_name
+            output_name = default_field_name
         elif len(tokens) == 2:
             step_id = tokens[0]
             output_name = tokens[1]
@@ -45,6 +49,10 @@ def create_step_value_address(
         step_id = value_address_config["step_id"]
         output_name = value_address_config["output_name"]
         sub_value = value_address_config.get("sub_value", None)
+    else:
+        raise TypeError(
+            f"Invalid type for creating step value address: {type(value_address_config)}"
+        )
 
     if sub_value is not None and not isinstance(sub_value, typing.Mapping):
         raise ValueError(
@@ -57,6 +65,30 @@ def create_step_value_address(
     return input_link
 
 
+def ensure_step_value_addresses(
+    link: typing.Union[str, typing.Mapping, typing.Iterable], default_field_name: str
+) -> typing.List[StepValueAddress]:
+
+    if isinstance(link, (str, typing.Mapping)):
+        input_links: typing.List[StepValueAddress] = [
+            create_step_value_address(
+                value_address_config=link, default_field_name=default_field_name
+            )
+        ]
+
+    elif isinstance(link, typing.Iterable):
+        input_links = []
+        for o in link:
+            il = create_step_value_address(
+                value_address_config=o, default_field_name=default_field_name
+            )
+            input_links.append(il)
+    else:
+        raise TypeError(f"Can't parse input map, invalid type for output: {link}")
+
+    return input_links
+
+
 class PipelineStepConfig(BaseModel):
     """A class to hold the configuration of one module within a [PipelineModule][kiara.pipeline.module.PipelineModule]."""
 
@@ -81,42 +113,45 @@ def ensure_input_links_valid(cls, v):
         result = {}
         for input_name, output in v.items():
 
-            if isinstance(output, (str, typing.Mapping)):
-                input_links = [
-                    create_step_value_address(
-                        value_address_config=output, field_name=input_name
-                    )
-                ]
-
-            elif isinstance(output, collections.abc.Sequence):
-                input_links = []
-                for o in output:
-                    il = create_step_value_address(
-                        value_address_config=o, field_name=input_name
-                    )
-                    input_links.append(il)
-            else:
-                raise TypeError(
-                    f"Can't parse input map, invalid type for output: {output}"
-                )
-
+            input_links = ensure_step_value_addresses(
+                default_field_name=input_name, link=output
+            )
             result[input_name] = input_links
 
         return result
 
 
+class PipelineStructureConfig(BaseModel):
+
+    parent_id: str = Field(description="The id of the parent of this structure.")
+    steps: typing.List[PipelineStepConfig]
+    input_aliases: typing.Union[None, str, typing.Dict[str, str]] = None
+    output_aliases: typing.Union[None, str, typing.Dict[str, str]] = None
+
+
 class KiaraModuleConfig(BaseModel):
-    """Base class that describes the configuration a [KiaraModule][kiara.module.KiaraModule] class accepts.
+    """Base class that describes the configuration a [``KiaraModule``][kiara.module.KiaraModule] class accepts.
 
     This is stored in the ``_config_cls`` class attribute in each ``KiaraModule`` class. By default,
     such a ``KiaraModule`` is not configurable.
 
+    There are two config options every ``KiaraModule`` supports:
+
+     - ``constants``, and
+     - ``defaults``
+
+     Constants are pre-set inputs, and users can't change them and an error is thrown if they try. Defaults are default
+     values that override the schema defaults, and those can be overwritten by users. If both a constant and a default
+     value is set for an input field, an error is thrown.
     """
 
     _config_hash: str = PrivateAttr(default=None)
     constants: typing.Dict[str, typing.Any] = Field(
         default_factory=dict, description="Value constants for this module."
     )
+    defaults: typing.Dict[str, typing.Any] = Field(
+        default_factory=dict, description="Value defaults for this module."
+    )
 
     class Config:
         extra = Extra.forbid
@@ -267,9 +302,7 @@ def create_structure(
 
         ps = PipelineStructure(
             parent_id=parent_id,
-            steps=self.steps,
-            input_aliases=self.input_aliases,
-            output_aliases=self.output_aliases,
+            config=self,
             kiara=kiara,
         )
         return ps
@@ -277,7 +310,6 @@ def create_structure(
     def create_pipeline(
         self,
         parent_id: typing.Optional[str] = None,
-        constants: typing.Optional[typing.Mapping[str, typing.Any]] = None,
         controller: typing.Optional["PipelineController"] = None,
         kiara: typing.Optional["Kiara"] = None,
     ):
@@ -290,7 +322,6 @@ def create_pipeline(
 
         pipeline = Pipeline(
             structure=structure,
-            constants=constants,
             controller=controller,
         )
         return pipeline
diff --git a/src/kiara/modules/metadata.py b/src/kiara/modules/metadata.py
new file mode 100644
index 000000000..55f5cfeee
--- /dev/null
+++ b/src/kiara/modules/metadata.py
@@ -0,0 +1,154 @@
+# -*- coding: utf-8 -*-
+import abc
+import typing
+from pydantic import BaseModel, Field
+
+from kiara import KiaraModule
+from kiara.data import Value, ValueSet
+from kiara.data.values import ValueSchema
+from kiara.exceptions import KiaraProcessingException
+from kiara.module_config import KiaraModuleConfig
+
+
+class MetadataModuleConfig(KiaraModuleConfig):
+
+    type: str = Field(description="The data type this module will be used for.")
+
+
+class ExtractMetadataModule(KiaraModule):
+    """Extract metadata for the 'table' type."""
+
+    _config_cls = MetadataModuleConfig
+
+    @classmethod
+    @abc.abstractmethod
+    def _get_supported_types(self) -> typing.Union[str, typing.Iterable[str]]:
+        pass
+
+    @classmethod
+    def get_metadata_key(cls) -> str:
+        return cls._module_type_name  # type: ignore
+
+    @classmethod
+    def get_supported_value_types(cls) -> typing.Set[str]:
+        _types = cls._get_supported_types()
+        if isinstance(_types, str):
+            _types = [_types]
+
+        return set(_types)
+
+    def __init__(self, *args, **kwargs):
+
+        self._metadata_schema: typing.Optional[str] = None
+        super().__init__(*args, **kwargs)
+
+    @property
+    def value_type(self) -> str:
+        data_type = self.get_config_value("type")
+        sup_types = self.get_supported_value_types()
+        if "*" not in sup_types and data_type not in sup_types:
+            raise ValueError(
+                f"Invalid module configuration, type '{data_type}' not supported. Supported types: {', '.join(self.get_supported_value_types())}."
+            )
+
+        return data_type
+
+    @property
+    def metadata_schema(self) -> str:
+        if self._metadata_schema is not None:
+            return self._metadata_schema
+
+        schema = self._get_metadata_schema(type=self.value_type)
+        if isinstance(schema, type) and issubclass(schema, BaseModel):
+            schema = schema.schema_json()
+        elif not isinstance(schema, str):
+            raise TypeError(f"Invalid type for metadata schema: {type(schema)}")
+
+        self._metadata_schema = schema
+        return self._metadata_schema
+
+    @abc.abstractmethod
+    def _get_metadata_schema(
+        self, type: str
+    ) -> typing.Union[str, typing.Type[BaseModel]]:
+        """Create the metadata schema for the configured type."""
+
+    @abc.abstractmethod
+    def extract_metadata(self, value: Value) -> typing.Mapping[str, typing.Any]:
+        pass
+
+    def create_input_schema(
+        self,
+    ) -> typing.Mapping[
+        str, typing.Union[ValueSchema, typing.Mapping[str, typing.Any]]
+    ]:
+
+        inputs = {
+            "value": {
+                "type": self.value_type,
+                "doc": f"A value of type '{self.value_type}'",
+                "optional": False,
+            }
+        }
+        return inputs
+
+    def create_output_schema(
+        self,
+    ) -> typing.Mapping[
+        str, typing.Union[ValueSchema, typing.Mapping[str, typing.Any]]
+    ]:
+        outputs = {
+            "metadata": {"type": "dict", "doc": "The metadata for the provided value."},
+            "metadata_schema": {
+                "type": "string",
+                "doc": "The (json) schema for the metadata.",
+            },
+        }
+
+        return outputs
+
+    def process(self, inputs: ValueSet, outputs: ValueSet) -> None:
+
+        value = inputs.get_value_obj("value")
+        if value.value_schema.type != self.value_type:
+            raise KiaraProcessingException(
+                f"Can't extract metadata for value of type '{value.value_schema.type}'. Expected type '{self.value_type}'."
+            )
+
+        outputs.set_value("metadata_schema", self.metadata_schema)
+        metadata = self.extract_metadata(value)
+        # TODO: validate metadata?
+        outputs.set_value("metadata", metadata)
+
+
+class ExtractPythonClass(ExtractMetadataModule):
+    @classmethod
+    def _get_supported_types(cls) -> typing.Union[str, typing.Iterable[str]]:
+        return "*"
+
+    @classmethod
+    def get_metadata_key(cls) -> str:
+        return "python_cls"
+
+    def _get_metadata_schema(
+        self, type: str
+    ) -> typing.Union[str, typing.Type[BaseModel]]:
+        class PythonClassModel(BaseModel):
+            class_name: str = Field(description="The name of the Python class")
+            module_name: str = Field(
+                description="The name of the Python module this class lives in."
+            )
+            full_name: str = Field(description="The full class namespace.")
+
+        return PythonClassModel
+
+    def extract_metadata(self, value: Value) -> typing.Mapping[str, typing.Any]:
+
+        item = value.get_value_data()
+        cls = item.__class__
+
+        return {
+            "class_name": cls.__name__,
+            "module_name": cls.__module__,
+            "full_name": f"{cls.__module__}.{cls.__name__}",
+        }
diff --git a/src/kiara/modules/type_conversion.py b/src/kiara/modules/type_conversion.py
new file mode 100644
index 000000000..e1e36591d
--- /dev/null
+++ b/src/kiara/modules/type_conversion.py
@@ -0,0 +1,128 @@
+# -*- coding: utf-8 -*-
+import abc
+import typing
+from pydantic import Field
+
+from kiara import KiaraModule
+from kiara.data.values import Value, ValueSchema, ValueSet
+from kiara.exceptions import KiaraProcessingException
+from kiara.module_config import KiaraModuleConfig
+
+
+class TypeConversionModuleConfig(KiaraModuleConfig):
+
+    source_type: str = Field(description="The source type.")
+    target_type: str = Field(description="The target type.")
+
+
+class TypeConversionModule(KiaraModule):
+
+    _config_cls = TypeConversionModuleConfig
+
+    @classmethod
+    @abc.abstractmethod
+    def _get_supported_source_types(self) -> typing.Union[typing.Iterable[str], str]:
+        pass
+
+    @classmethod
+    @abc.abstractmethod
+    def _get_target_types(self) -> typing.Union[typing.Iterable[str], str]:
+        pass
+
+    @classmethod
+    def get_supported_source_types(self) -> typing.Set[str]:
+
+        _types: typing.Iterable[str] = self._get_supported_source_types()
+        if isinstance(_types, str):
+            _types = [_types]
+
+        if "config" in _types:
+            raise Exception("Invalid source type, type name 'config' is invalid.")
+        return set(_types)
+
+    @classmethod
+    def get_supported_target_types(self) -> typing.Set[str]:
+
+        _types: typing.Iterable[str] = self._get_target_types()
+        if isinstance(_types, str):
+            _types = [_types]
+        return set(_types)
+
+    def __init__(self, *args, **kwargs):
+
+        super().__init__(*args, **kwargs)
+
+    @property
+    def source_type(self) -> str:
+        data_type = self.get_config_value("source_type")
+        supported = self.get_supported_source_types()
+        if "*" not in supported and data_type not in supported:
+            raise ValueError(
+                f"Invalid module configuration, source type '{data_type}' not supported. Supported types: {', '.join(self.get_supported_source_types())}."
+            )
+
+        return data_type
+
+    @property
+    def target_type(self) -> str:
+        data_type = self.get_config_value("target_type")
+        if data_type not in self.get_supported_target_types():
+            raise ValueError(
+                f"Invalid module configuration, target type '{data_type}' not supported. Supported types: {', '.join(self.get_supported_target_types())}."
+            )
+
+        return data_type
+
+    def create_input_schema(
+        self,
+    ) -> typing.Mapping[
+        str, typing.Union[ValueSchema, typing.Mapping[str, typing.Any]]
+    ]:
+
+        inputs: typing.Mapping[str, typing.Any] = {
+            "source_value": {
+                "type": self.source_type,
+                "doc": f"A value of type '{self.source_type}'.",
+            },
+            "config": {
+                "type": "dict",
+                "doc": "The configuration for the transformation.",
+                "optional": True,
+            },
+        }
+
+        return inputs
+
+    def create_output_schema(
+        self,
+    ) -> typing.Mapping[
+        str, typing.Union[ValueSchema, typing.Mapping[str, typing.Any]]
+    ]:
+        outputs = {
+            "target_value": {
+                "type": self.target_type,
+                "doc": f"A value of type '{self.target_type}'.",
+            }
+        }
+        return outputs
+
+    def process(self, inputs: ValueSet, outputs: ValueSet) -> None:
+
+        value = inputs.get_value_obj("source_value")
+        if value.value_schema.type != self.source_type:
+            raise KiaraProcessingException(
+                f"Can't convert value of source type '{value.value_schema.type}'. Expected type '{self.source_type}'."
+            )
+        config = inputs.get_value_data("config")
+        if config is None:
+            config = {}
+
+        target_value = self.convert(value=value, config=config)
+        # TODO: validate value?
+        outputs.set_value("target_value", target_value)
+
+    @abc.abstractmethod
+    def convert(
+        self, value: Value, config: typing.Mapping[str, typing.Any]
+    ) -> typing.Any:
+        pass
diff --git a/src/kiara/pipeline/module.py b/src/kiara/pipeline/module.py
index 3f3bb0725..c829be530 100644
--- a/src/kiara/pipeline/module.py
+++ b/src/kiara/pipeline/module.py
@@ -59,7 +59,6 @@ def __init__(
         if controller is None:
             controller = BatchController()
 
-        self._pipeline_structure: typing.Optional[PipelineStructure] = None
         self._pipeline_controller: PipelineController = controller
         super().__init__(
             id=id,
@@ -68,21 +67,23 @@ def __init__(
             meta=meta,
             kiara=kiara,
         )
+        self._pipeline_structure: PipelineStructure = self._create_structure()
+        assert not self._config.constants
+        self._config.constants = dict(self._pipeline_structure.constants)
 
     @property
     def structure(self) -> PipelineStructure:
         """The ``PipelineStructure`` of this module."""
 
-        if self._pipeline_structure is None:
-            self._pipeline_structure = PipelineStructure(
-                parent_id=self.full_id,
-                steps=self._config.steps,
-                input_aliases=self._config.input_aliases,
-                output_aliases=self._config.output_aliases,
-                kiara=self._kiara,
-            )
         return self._pipeline_structure
 
+    def _create_structure(self) -> PipelineStructure:
+
+        pipeline_structure = PipelineStructure(
+            parent_id=self.full_id, config=self.config, kiara=self._kiara
+        )
+        return pipeline_structure
+
     def create_input_schema(self) -> typing.Mapping[str, ValueSchema]:
         return self.structure.pipeline_input_schema
 
diff --git a/src/kiara/pipeline/pipeline.py b/src/kiara/pipeline/pipeline.py
index 845005b8d..054668f72 100644
--- a/src/kiara/pipeline/pipeline.py
+++ b/src/kiara/pipeline/pipeline.py
@@ -58,7 +58,7 @@ class Pipeline(object):
     def __init__(
         self,
         structure: PipelineStructure,
-        constants: typing.Optional[typing.Mapping[str, typing.Any]] = None,
+        # constants: typing.Optional[typing.Mapping[str, typing.Any]] = None,
         controller: typing.Optional[PipelineController] = None,
     ):
 
@@ -75,10 +75,6 @@ def __init__(
 
         self._kiara: Kiara = self._structure._kiara
 
-        if constants is None:
-            constants = {}
-        self._constants: typing.Mapping[str, typing.Any] = constants
-
         self._data_registry: DataRegistry = self._kiara.data_registry
 
         self._init_values()
@@ -226,15 +222,26 @@ def _init_values(self):
                         # if the pipeline input wasn't created by another step input before,
                         # we need to take care of it here
 
-                        constant = self._constants.get(
-                            connected_pipeline_input_name, None
-                        )
+                        if pipeline_input_field.is_constant:
+                            init_value = self.structure.constants[
+                                pipeline_input_field.value_name
+                            ]
+                            origin = f"pipeline_input:{self.structure.pipeline_id}.{input_name} (constant)"
+                        else:
+                            init_value = self.structure.defaults.get(
+                                pipeline_input_field.value_name, None
+                            )
+                            if init_value is not None:
+                                origin = f"pipeline_input:{self.structure.pipeline_id}.{input_name} (default)"
+                            else:
+                                origin = f"pipeline_input:{self.structure.pipeline_id}.{input_name}"
+
                         pipeline_input = self._data_registry.register_value(
                             value_schema=pipeline_input_field.value_schema,
                             value_fields=pipeline_input_field,
-                            is_constant=False if constant is None else True,
-                            initial_value=constant,
-                            origin=f"pipeline_input:{self.structure.pipeline_id}.{input_name}",
+                            is_constant=pipeline_input_field.is_constant,
+                            initial_value=init_value,
+                            origin=origin,
                         )
                         self._data_registry.register_callback(
                             self.values_updated, pipeline_input
diff --git a/src/kiara/pipeline/structure.py b/src/kiara/pipeline/structure.py
index 7c103254f..b348e6a68 100644
--- a/src/kiara/pipeline/structure.py
+++ b/src/kiara/pipeline/structure.py
@@ -2,9 +2,10 @@
 import networkx as nx
 import typing
 import uuid
+from bidict import frozenbidict
 from functools import lru_cache
 from networkx import NetworkXNoPath, NodeNotFound
-from pydantic import BaseModel, Extra, Field, PrivateAttr
+from pydantic import BaseModel, Extra, Field, PrivateAttr, validator
 from rich import box
 from rich.console import Console, ConsoleOptions, RenderGroup, RenderResult
 from rich.markdown import Markdown
@@ -22,10 +23,12 @@
 )
 from kiara.defaults import DEFAULT_NO_DESC_VALUE, PIPELINE_PARENT_MARKER, SpecialValue
 from kiara.module import KiaraModule
+from kiara.pipeline.utils import create_pipeline_structure_desc, extend_pipeline
 
 if typing.TYPE_CHECKING:
     from kiara.kiara import Kiara
-    from kiara.module_config import PipelineStepConfig
+    from kiara.module_config import PipelineModuleConfig, PipelineStepConfig
+    from kiara.pipeline.pipeline import Pipeline
 
 
 class PipelineStep(BaseModel):
@@ -62,6 +65,15 @@ def create_steps(
 
     _module: typing.Optional[KiaraModule] = PrivateAttr(default=None)
 
+    @validator("step_id")
+    def _validate_step_id(cls, v):
+
+        assert isinstance(v, str)
+        if "." in v:
+            raise ValueError("Step ids can't contain '.' characters.")
+
+        return v
+
     step_id: str
     parent_id: str
     module_type: str = Field(description="The module type.")
@@ -235,13 +247,16 @@ class PipelineStructure(object):
     def __init__(
         self,
         parent_id: str,
-        steps: typing.Iterable["PipelineStepConfig"],
-        input_aliases: typing.Union[str, typing.Mapping[str, str]] = None,
-        output_aliases: typing.Union[str, typing.Mapping[str, str]] = None,
-        add_all_workflow_outputs: bool = False,
+        config: "PipelineModuleConfig",
         kiara: typing.Optional["Kiara"] = None,
     ):
 
+        self._structure_config: "PipelineModuleConfig" = config
+
+        steps = self._structure_config.steps
+        input_aliases = self._structure_config.input_aliases
+        output_aliases = self._structure_config.output_aliases
+
         if not steps:
             raise Exception("No steps provided.")
 
@@ -276,12 +291,16 @@ def __init__(
                 self._steps, output_aliases, "outputs"
             )
 
-        self._input_aliases: typing.Mapping[str, str] = input_aliases  # type: ignore
+        self._input_aliases: frozenbidict[str, str] = frozenbidict(input_aliases)  # type: ignore
         if output_aliases is None:
             output_aliases = {}
-        self._output_aliases: typing.Mapping[str, str] = output_aliases  # type: ignore
+        self._output_aliases: frozenbidict[str, str] = frozenbidict(output_aliases)  # type: ignore
 
-        self._add_all_workflow_outputs: bool = add_all_workflow_outputs
+        # this is hardcoded for now
+        self._add_all_workflow_outputs: bool = False
+
+        self._constants: typing.Dict[str, typing.Any] = None  # type: ignore
+        self._defaults: typing.Dict[str, typing.Any] = None  # type: ignore
 
         self._execution_graph: nx.DiGraph = None  # type: ignore
         self._data_flow_graph: nx.DiGraph = None  # type: ignore
@@ -296,6 +315,10 @@ def __init__(
     def pipeline_id(self) -> str:
         return self._pipeline_id
 
+    @property
+    def structure_config(self) -> "PipelineModuleConfig":
+        return self._structure_config
+
     @property
     def steps(self) -> typing.Iterable[PipelineStep]:
         return self._steps
@@ -317,6 +340,20 @@ def step_ids(self) -> typing.Iterable[str]:
             self._process_steps()
         return self._steps_details.keys()
 
+    @property
+    def constants(self) -> typing.Mapping[str, typing.Any]:
+
+        if self._constants is None:
+            self._process_steps()
+        return self._constants
+
+    @property
+    def defaults(self) -> typing.Mapping[str, typing.Any]:
+
+        if self._defaults is None:
+            self._process_steps()
+        return self._defaults
+
     def get_step(self, step_id: str) -> PipelineStep:
 
         d = self.steps_details.get(step_id, None)
@@ -436,6 +473,8 @@ def _process_steps(self):
         data_flow_graph = nx.DiGraph()
         data_flow_graph_simple = nx.DiGraph()
         processing_stages = []
+        constants = {}
+        structure_defaults = {}
 
         # temp variable, to hold all outputs
         outputs: typing.Dict[str, StepOutputField] = {}
@@ -518,9 +557,16 @@ def _process_steps(self):
             other_step_dependency: typing.Set = set()
             # go through all the inputs of a module, create input points and connect them to either
             # other module outputs, or pipeline inputs (which need to be created)
+
+            module_constants: typing.Mapping[
+                str, typing.Any
+            ] = step.module.get_config_value("constants")
+
             for input_name, schema in step.module.input_schemas.items():
 
                 matching_input_links: typing.List[StepValueAddress] = []
+                is_constant = input_name in module_constants.keys()
+
                 for value_name, input_links in step.input_links.items():
                     if value_name == input_name:
                         for input_link in input_links:
@@ -541,7 +587,7 @@ def _process_steps(self):
 
                         if output_id not in outputs.keys():
                             raise Exception(
-                                f"Can't connect input '{input_name}' for step '{step.step_id}': no output '{output_id}' available."
+                                f"Can't connect input '{input_name}' for step '{step.step_id}': no output '{output_id}' available. Available output names: {', '.join(outputs.keys())}"
                             )
                         connected_output_points.append(outputs[output_id])
                         connected_outputs.append(input_link)
@@ -553,6 +599,7 @@ def _process_steps(self):
                         pipeline_id=self._pipeline_id,
                         value_name=input_name,
                         value_schema=schema,
+                        is_constant=is_constant,
                         connected_pipeline_input=None,
                         connected_outputs=connected_outputs,
                     )
@@ -572,6 +619,7 @@ def _process_steps(self):
                     pipeline_input_name = generate_pipeline_endpoint_name(
                         step_id=step.step_id, value_name=input_name
                     )
+                    # check whether this input has an alias associated with it
                     if self._input_aliases:
                         if pipeline_input_name in self._input_aliases.keys():
                             # this means we use the pipeline alias
@@ -585,12 +633,14 @@ def _process_steps(self):
                         connected_pipeline_input = existing_pipeline_input_points[
                             pipeline_input_name
                         ]
+                        assert connected_pipeline_input.is_constant == is_constant
                     else:
                         # we need to create the pipeline input
                         connected_pipeline_input = PipelineInputField(
                             value_name=pipeline_input_name,
                             value_schema=schema,
                             pipeline_id=self._pipeline_id,
+                            is_constant=is_constant,
                         )
 
                         existing_pipeline_input_points[
@@ -603,6 +653,20 @@ def _process_steps(self):
                         data_flow_graph_simple.add_node(
                             connected_pipeline_input, type=PipelineInputField.__name__
                         )
+                        if is_constant:
+                            constants[
+                                pipeline_input_name
+                            ] = step.module.get_config_value("constants")[input_name]
+
+                        default_val = step.module.get_config_value("defaults").get(
+                            input_name, None
+                        )
+                        if is_constant and default_val is not None:
+                            raise Exception(
+                                f"Module config invalid for step '{step.step_id}': both default value and constant provided for input '{input_name}'."
+                            )
+                        elif default_val is not None:
+                            structure_defaults[pipeline_input_name] = default_val
 
                     step_input_point = StepInputField(
                         step_id=step.step_id,
@@ -652,6 +716,8 @@ def _process_steps(self):
                 steps_details[_step_id]["processing_stage"] = i
                 steps_details[_step_id]["step"].processing_stage = i
 
+        self._constants = constants
+        self._defaults = structure_defaults
         self._steps_details = steps_details
         self._execution_graph = execution_graph
         self._data_flow_graph = data_flow_graph
@@ -716,64 +782,24 @@ def _process_steps(self):
             if optional:
                 inp.value_schema.optional = True
 
-    def to_details(self) -> "PipelineStructureDesc":
-
-        steps = {}
-        workflow_inputs: typing.Dict[str, typing.List[str]] = {}
-        workflow_outputs: typing.Dict[str, str] = {}
-
-        for m_id, details in self.steps_details.items():
-
-            step = details["step"]
-
-            input_connections: typing.Dict[str, typing.List[str]] = {}
-            for k, v in details["inputs"].items():
-
-                if v.connected_pipeline_input is not None:
-                    connected_item = v.connected_pipeline_input
-                    input_connections[k] = [
-                        generate_step_alias(PIPELINE_PARENT_MARKER, connected_item)
-                    ]
-                    workflow_inputs.setdefault(f"{connected_item}", []).append(v.alias)
-                elif v.connected_outputs is not None:
-                    assert len(v.connected_outputs) > 0
-                    for co in v.connected_outputs:
-                        input_connections.setdefault(k, []).append(co.alias)
-                else:
-                    raise TypeError(f"Invalid connection type: {type(connected_item)}")
-
-            output_connections: typing.Dict[str, typing.Any] = {}
-            for k, v in details["outputs"].items():
-                for connected_item in v.connected_inputs:
+    def extend(
+        self,
+        other: typing.Union[
+            "Pipeline",
+            "PipelineStructure",
+            "PipelineModuleConfig",
+            typing.Mapping[str, typing.Any],
+        ],
+        input_links: typing.Optional[
+            typing.Mapping[str, typing.Iterable[StepValueAddress]]
+        ] = None,
+    ) -> "PipelineStructure":
+
+        return extend_pipeline(self, other)
 
-                    output_connections.setdefault(k, []).append(
-                        generate_step_alias(
-                            connected_item.step_id, connected_item.value_name
-                        )
-                    )
-                if v.pipeline_output:
-                    output_connections.setdefault(k, []).append(
-                        generate_step_alias(PIPELINE_PARENT_MARKER, v.pipeline_output)
-                    )
-                    workflow_outputs[v.pipeline_output] = v.alias
-
-            steps[step.step_id] = StepDesc(
-                step=step,
-                processing_stage=details["processing_stage"],
-                input_connections=input_connections,
-                output_connections=output_connections,
-                required=step.required,
-            )
+    def to_details(self) -> "PipelineStructureDesc":
 
-        return PipelineStructureDesc(
-            pipeline_id=self._pipeline_id,
-            steps=steps,
-            processing_stages=self.processing_stages,
-            pipeline_input_connections=workflow_inputs,
-            pipeline_output_connections=workflow_outputs,
-            pipeline_inputs=self.pipeline_inputs,
-            pipeline_outputs=self.pipeline_outputs,
-        )
+        return create_pipeline_structure_desc(self)
 
     def __rich_console__(
         self, console: Console, options: ConsoleOptions
diff --git a/src/kiara/pipeline/utils.py b/src/kiara/pipeline/utils.py
new file mode 100644
index 000000000..a1987226f
--- /dev/null
+++ b/src/kiara/pipeline/utils.py
@@ -0,0 +1,211 @@
+# -*- coding: utf-8 -*-
+import typing
+from bidict import bidict
+
+from kiara.data.values import StepValueAddress, generate_step_alias
+from kiara.defaults import PIPELINE_PARENT_MARKER
+
+if typing.TYPE_CHECKING:
+    from kiara.module_config import PipelineModuleConfig
+    from kiara.pipeline.pipeline import Pipeline
+    from kiara.pipeline.structure import PipelineStructure, PipelineStructureDesc
+
+
+def create_pipeline_structure_desc(
+    pipeline: typing.Union["Pipeline", "PipelineStructure"]
+) -> "PipelineStructureDesc":
+
+    from kiara.pipeline.pipeline import Pipeline
+    from kiara.pipeline.structure import (
+        PipelineStructure,
+        PipelineStructureDesc,
+        StepDesc,
+    )
+
+    if isinstance(pipeline, Pipeline):
+        structure: PipelineStructure = pipeline.structure
+    elif isinstance(pipeline, PipelineStructure):
+        structure = pipeline
+
+    steps = {}
+    workflow_inputs: typing.Dict[str, typing.List[str]] = {}
+    workflow_outputs: typing.Dict[str, str] = {}
+
+    for m_id, details in structure.steps_details.items():
+
+        step = details["step"]
+
+        input_connections: typing.Dict[str, typing.List[str]] = {}
+        for k, v in details["inputs"].items():
+
+            if v.connected_pipeline_input is not None:
+                connected_item = v.connected_pipeline_input
+                input_connections[k] = [
+                    generate_step_alias(PIPELINE_PARENT_MARKER, connected_item)
+                ]
+                workflow_inputs.setdefault(f"{connected_item}", []).append(v.alias)
+            elif v.connected_outputs is not None:
+                assert len(v.connected_outputs) > 0
+                for co in v.connected_outputs:
+                    input_connections.setdefault(k, []).append(co.alias)
+            else:
+                raise TypeError(f"Invalid connection type: {type(connected_item)}")
+
+        output_connections: typing.Dict[str, typing.Any] = {}
+        for k, v in details["outputs"].items():
+            for connected_item in v.connected_inputs:
+
+                output_connections.setdefault(k, []).append(
+                    generate_step_alias(
+                        connected_item.step_id, connected_item.value_name
+                    )
+                )
+            if v.pipeline_output:
+                output_connections.setdefault(k, []).append(
+                    generate_step_alias(PIPELINE_PARENT_MARKER, v.pipeline_output)
+                )
+                workflow_outputs[v.pipeline_output] = v.alias
+
+        steps[step.step_id] = StepDesc(
+            step=step,
+            processing_stage=details["processing_stage"],
+            input_connections=input_connections,
+            output_connections=output_connections,
+            required=step.required,
+        )
+
+    return PipelineStructureDesc(
+        pipeline_id=structure._pipeline_id,
+        steps=steps,
+        processing_stages=structure.processing_stages,
+        pipeline_input_connections=workflow_inputs,
+        pipeline_output_connections=workflow_outputs,
+        pipeline_inputs=structure.pipeline_inputs,
+        pipeline_outputs=structure.pipeline_outputs,
+    )
+
+
+def extend_pipeline(
+    pipeline: typing.Union["Pipeline", "PipelineStructure"],
+    other: typing.Union[
+        "Pipeline",
+        "PipelineStructure",
+        "PipelineModuleConfig",
+        typing.Mapping[str, typing.Any],
+    ],
+    input_links: typing.Optional[
+        typing.Mapping[str, typing.Iterable[StepValueAddress]]
+    ] = None,
+):
+
+    from kiara.module_config import PipelineModuleConfig
+    from kiara.pipeline.pipeline import Pipeline
+    from kiara.pipeline.structure import PipelineStructure
+
+    if isinstance(pipeline, Pipeline):
+        structure: PipelineStructure = pipeline.structure
+    elif isinstance(pipeline, PipelineStructure):
+        structure = pipeline
+
+    other_pipeline_config: typing.Optional[PipelineModuleConfig] = None
+
+    other_name = "extended"
+
+    if isinstance(other, typing.Mapping):
+        other_pipeline_config = PipelineModuleConfig(**other)
+    elif isinstance(other, PipelineModuleConfig):
+        other_pipeline_config = other
+    elif isinstance(other, PipelineStructure):
+        other_pipeline_config = other.structure_config
+        other_name = other.pipeline_id
+
+    if other_pipeline_config is None:
+        from kiara.pipeline.pipeline import Pipeline
+
+        if isinstance(other, Pipeline):
+            other_pipeline_config = other.structure.structure_config
+
+    if other_pipeline_config is None:
+        raise TypeError(
+            f"Can't extend pipeline structure, invalid type: {type(other)}."
+        )
+
+    other_structure: PipelineStructure = PipelineStructure(
+        parent_id="_", config=other_pipeline_config, kiara=structure._kiara
+    )
+
+    step_id_overlap = [
+        el for el in set(structure.step_ids) if el in other_structure.step_ids
+    ]
+    if step_id_overlap:
+        raise Exception(
+            f"Can't extend pipeline, duplicate step id(s) are not allowed: {', '.join(step_id_overlap)}."
+        )
+
+    if input_links is None:
+        input_links = {}
+    else:
+        input_links = dict(input_links)
+
+    full_input_links: typing.Dict[
+        str, typing.Dict[str, typing.Iterable[StepValueAddress]]
+    ] = {}
+    for input_name, input in other_structure.pipeline_inputs.items():
+        if input_name not in input_links.keys():
+            # this means we try to see whether there is an output in this structure with the same name
+            if input_name in structure.pipeline_outputs.keys():
+                output_step_address: typing.Iterable[StepValueAddress] = [
+                    structure.pipeline_outputs[input_name].connected_output
+                ]
+            else:
+                # output_step_address = "NEW INPUT"
+                raise NotImplementedError()
+        else:
+            output_step_address = input_links[input_name]
+
+        connected_inputs = other_structure.pipeline_inputs[input_name].connected_inputs
+        if len(connected_inputs) != 1:
+            raise NotImplementedError()
+        else:
+            connected_input = connected_inputs[0]
+            full_input_links.setdefault(connected_input.step_id, {})[
+                connected_input.value_name
+            ] = output_step_address
+
+    new_input_aliases = bidict(structure._input_aliases)
+    if not other_structure._output_aliases:
+        new_output_aliases: typing.Union[str, typing.Mapping[str, str]] = "auto"
+    else:
+        new_output_aliases = bidict(other_structure._output_aliases)
+
+    config = structure.structure_config.dict(
+        exclude={"input_aliases", "output_aliases", "steps"}
+    )
+    config["input_aliases"] = new_input_aliases
+    config["output_aliases"] = new_output_aliases
+
+    new_steps = [
+        step.dict(exclude={"parent_id", "processing_stage", "required"})
+        for step in structure.steps
+    ]
+
+    for step in other_structure.steps:
+        step_dict = step.dict(exclude={"parent_id", "processing_stage", "required"})
+        if step.step_id in full_input_links.keys():
+            if step.step_id not in full_input_links.keys():
+                new_steps.append(step_dict)
+            else:
+                for input_name in full_input_links[step.step_id].keys():
+                    if input_name in step_dict["input_links"].keys():
+                        raise NotImplementedError()
+                    step_dict["input_links"][input_name] = full_input_links[
+                        step.step_id
+                    ][input_name]
+                new_steps.append(step_dict)
+
+    config["steps"] = new_steps
+    pmc = PipelineModuleConfig(**config)
+    new_structure = pmc.create_structure(
+        f"{structure.pipeline_id}_{other_name}", kiara=structure._kiara
+    )
+    return new_structure
diff --git a/src/kiara/profiles.py b/src/kiara/profiles.py
new file mode 100644
index 000000000..c90bcf506
--- /dev/null
+++ b/src/kiara/profiles.py
@@ -0,0 +1,197 @@
+# -*- coding: utf-8 -*-
+import typing
+from pydantic import BaseModel, Extra, Field, PrivateAttr
+
+if typing.TYPE_CHECKING:
+    from kiara import Kiara
+    from kiara.module import KiaraModule
+
+
+class ModuleProfileConfig(BaseModel):
+    class Config:
+        extra = Extra.forbid
+        validate_all = True
+
+    _module: typing.Optional["KiaraModule"] = PrivateAttr(default=None)
+    module_type: str = Field(description="The module type.")
+    module_config: typing.Dict[str, typing.Any] = Field(
+        default_factory=dict, description="The configuration for the module."
+    )
+
+    def create_module(self, kiara: "Kiara"):
+
+        if self._module is None:
+            self._module = kiara.create_module(
+                id=f"extract_metadata_{self.module_type}",
+                module_type=self.module_type,
+                module_config=self.module_config,
+            )
+        return self._module
+
+
+class TypeConversionProfileConfig(ModuleProfileConfig):
+
+    convert_source_type: str = Field(description="The source type.")
+    convert_target_type: str = Field(description="The target type.")
+    doc: str = Field(
+        description="Documentation of what this profile does/is appropriate for.",
+        default="-- n/a --",
+    )
+
+
+class ExtractMetadataProfileConfig(ModuleProfileConfig):
+
+    value_type: str = Field(
+        description="The type of the value to extract metadata from."
+    )
+
+
+class ModuleProfileMgmt(object):
+    def __init__(self, kiara: "Kiara"):
+
+        self._kiara: "Kiara" = kiara
+        self._convert_profiles: typing.Dict[
+            str, typing.Dict[str, TypeConversionProfileConfig]
+        ] = None  # type: ignore
+        self._metadata_profiles: typing.Dict[
+            str, typing.Dict[str, ExtractMetadataProfileConfig]
+        ] = None  # type: ignore
+
+    @property
+    def extract_metadata_profiles(
+        self,
+    ) -> typing.Mapping[str, typing.Mapping[str, ExtractMetadataProfileConfig]]:
+
+        if self._metadata_profiles is not None:
+            return self._metadata_profiles
+
+        from kiara.modules.metadata import ExtractMetadataModule
+
+        all_metadata_profiles = {}
+        for module_type in self._kiara.available_module_types:
+
+            cls = self._kiara.get_module_class(module_type=module_type)
+
+            if issubclass(cls, ExtractMetadataModule):
+                value_types = cls.get_supported_value_types()
+                if "*" in value_types:
+                    value_types = self._kiara._type_mgmt.value_type_names
+                metadata_key = cls.get_metadata_key()
+
+                for value_type in value_types:
+                    if (
+                        metadata_key
+                        in all_metadata_profiles.setdefault(value_type, {}).keys()
+                    ):
+                        raise Exception(
+                            f"Multiple profiles for type '{value_type}' and metadata key '{metadata_key}'. This is not allowed."
+                        )  # yet, anyway
+
+                    mc = {"type": value_type}
+                    all_metadata_profiles[value_type][
+                        metadata_key
+                    ] = ExtractMetadataProfileConfig(
+                        module_type=module_type, module_config=mc, value_type=value_type
+                    )
+
+            if hasattr(cls, "_extract_metadata_profiles"):
+                profiles: typing.Mapping[str, typing.Mapping[str, typing.Any]] = cls._convert_profiles  # type: ignore
+                for value_type, extract_details in profiles.items():
+                    for metadata_key, module_config in extract_details.items():
+                        if (
+                            metadata_key
+                            in all_metadata_profiles.setdefault(value_type, {}).keys()
+                        ):
+                            raise Exception(
+                                f"Multiple profiles for type '{value_type}' and metadata key '{metadata_key}'. This is not allowed."
+                            )  # yet, anyway
+                        all_metadata_profiles[value_type][
+                            metadata_key
+                        ] = ExtractMetadataProfileConfig(
+                            module_type=module_type,
+                            module_config=module_config,
+                            value_type=value_type,
+                        )
+
+        self._metadata_profiles = all_metadata_profiles
+        return self._metadata_profiles
+
+    @property
+    def type_convert_profiles(
+        self,
+    ) -> typing.Mapping[str, typing.Mapping[str, TypeConversionProfileConfig]]:
+
+        if self._convert_profiles is not None:
+            return self._convert_profiles
+
+        from kiara.modules.type_conversion import TypeConversionModule
+
+        all_convert_profiles = {}
+        for module_type in self._kiara.available_module_types:
+            cls = self._kiara.get_module_class(module_type=module_type)
+
+            if issubclass(cls, TypeConversionModule):
+                source_types = cls.get_supported_source_types()
+                if "*" in source_types:
+                    source_types = self._kiara._type_mgmt.value_type_names
+                target_types = cls.get_supported_target_types()
+
+                for source_type in source_types:
+                    for target_type in target_types:
+                        if (
+                            target_type
+                            in all_convert_profiles.setdefault(source_type, {}).keys()
+                        ):
+                            raise Exception(
+                                f"Multiple convert targets for '{source_type} -> {target_type}', this is not allowed."
+                            )  # yet, anyway
+                        mc = {"source_type": source_type, "target_type": target_type}
+                        all_convert_profiles[source_type][
+                            target_type
+                        ] = TypeConversionProfileConfig(
+                            module_type=module_type,
+                            module_config=mc,
+                            convert_source_type=source_type,
+                            convert_target_type=target_type,
+                        )
+
+            if hasattr(cls, "_convert_profiles"):
+                profiles: typing.Mapping[str, typing.Mapping[str, typing.Any]] = cls._convert_profiles  # type: ignore
+                for source_type, module_config in profiles.items():
+                    for target_type, details in module_config.items():
+                        if (
+                            target_type
+                            in all_convert_profiles.setdefault(source_type, {}).keys()
+                        ):
+                            raise Exception(
+                                f"Multiple convert targets for '{source_type} -> {target_type}', this is not allowed."
+                            )  # yet, anyway
+                        all_convert_profiles[source_type][
+                            target_type
+                        ] = TypeConversionProfileConfig(
+                            module_type=module_type,
+                            module_config=module_config,
+                            convert_source_type=source_type,
+                            convert_target_type=target_type,
+                        )
+
+        self._convert_profiles = all_convert_profiles
+        return self._convert_profiles
+
+    def get_type_conversion_module(
+        self, source_type: str, target_type: str
+    ) -> "KiaraModule":
+
+        all_source_profiles = self.type_convert_profiles.get(source_type, None)
+        if not all_source_profiles:
+            raise Exception(
+                f"No type conversion profiles for source type '{source_type}'."
+            )
+
+        convert_profile = all_source_profiles.get(target_type, None)
+        if not convert_profile:
+            raise Exception(
+                f"No target conversion profile '{target_type}' for source type '{source_type}' available."
+            )
+
+        return convert_profile.create_module(self._kiara)
diff --git a/src/kiara/utils/__init__.py b/src/kiara/utils/__init__.py
index 3380214a2..9667aa904 100644
--- a/src/kiara/utils/__init__.py
+++ b/src/kiara/utils/__init__.py
@@ -16,6 +16,7 @@
     model_process_schema,
 )
 from rich import box
+from rich.console import ConsoleRenderable, RichCast
 from rich.table import Table
 from ruamel.yaml import YAML
 from types import ModuleType
@@ -48,6 +49,10 @@ def log_message(msg: str):
         log.debug(msg)
 
 
+def is_rich_renderable(item: typing.Any):
+    return isinstance(item, (ConsoleRenderable, RichCast, str))
+
+
 def get_data_from_file(
     path: Union[str, Path], content_type: typing.Optional[str] = None
 ) -> typing.Any:
@@ -160,6 +165,7 @@ def create_table_from_field_schemas(
     _add_default: bool = True,
     _add_required: bool = True,
     _show_header: bool = False,
+    _constants: typing.Optional[typing.Mapping[str, typing.Any]] = None,
     **fields: "ValueSchema",
 ):
 
@@ -167,10 +173,14 @@ def create_table_from_field_schemas(
     table.add_column("Field name", style="i")
     table.add_column("Type")
     table.add_column("Description")
+
     if _add_required:
         table.add_column("Required")
     if _add_default:
-        table.add_column("Default")
+        if _constants:
+            table.add_column("Default / Constant")
+        else:
+            table.add_column("Default")
 
     for field_name, schema in fields.items():
 
@@ -192,10 +202,17 @@ def create_table_from_field_schemas(
             row.append(req_str)
 
         if _add_default:
-            if schema.default in [None, SpecialValue.NO_VALUE, SpecialValue.NOT_SET]:
-                d = "-- no default --"
+            if _constants and field_name in _constants.keys():
+                d = f"[b]{_constants[field_name]}[/b] (constant)"
             else:
-                d = str(schema.default)
+                if schema.default in [
+                    None,
+                    SpecialValue.NO_VALUE,
+                    SpecialValue.NOT_SET,
+                ]:
+                    d = "-- no default --"
+                else:
+                    d = str(schema.default)
             row.append(d)
 
         table.add_row(*row)
diff --git a/src/kiara/utils/class_loading.py b/src/kiara/utils/class_loading.py
index 0c5a8f251..e018e5145 100644
--- a/src/kiara/utils/class_loading.py
+++ b/src/kiara/utils/class_loading.py
@@ -185,6 +185,7 @@ def find_all_kiara_modules() -> typing.Dict[str, typing.Type["KiaraModule"]]:
         if isinstance(plugin.plugin, type) and issubclass(plugin.plugin, KiaraModule):
             ep = plugin.entry_point
             module_cls = ep.load()
+            setattr(module_cls, "_module_type_name", name)
             result_entrypoints[name] = module_cls
         elif (
             isinstance(plugin.plugin, tuple)
diff --git a/src/kiara/utils/output.py b/src/kiara/utils/output.py
new file mode 100644
index 000000000..3e981c49b
--- /dev/null
+++ b/src/kiara/utils/output.py
@@ -0,0 +1,178 @@
+# -*- coding: utf-8 -*-
+import typing
+from pyarrow import Table
+from pydantic import BaseModel, Field, root_validator
+from rich import box
+from rich.console import RenderableType
+from rich.table import Table as RichTable
+
+from kiara.utils import dict_from_cli_args
+
+
+class OutputDetails(BaseModel):
+    @classmethod
+    def from_data(cls, data: typing.Any):
+
+        if isinstance(data, str):
+            if "=" in data:
+                data = [data]
+            else:
+                data = [f"format={data}"]
+
+        if isinstance(data, typing.Iterable):
+            data = list(data)
+            if len(data) == 1 and isinstance(data[0], str) and "=" not in data[0]:
+                data = [f"format={data[0]}"]
+            output_details_dict = dict_from_cli_args(*data)
+        else:
+            raise TypeError(
+                f"Can't parse output detail config: invalid input type '{type(data)}'."
+            )
+
+        output_details = OutputDetails(**output_details_dict)
+        return output_details
+
+    format: str = Field(description="The output format.")
+    target: str = Field(description="The output target.")
+    config: typing.Dict[str, typing.Any] = Field(
+        description="Output configuration.", default_factory=dict
+    )
+
+    @root_validator(pre=True)
+    def _set_defaults(cls, values):
+
+        target: str = values.pop("target", "terminal")
+        format: str = values.pop("format", None)
+        if format is None:
+            if target == "terminal":
+                format = "terminal"
+            else:
+                if target == "file":
+                    format = "json"
+                else:
+                    ext = target.split(".")[-1]
+                    if ext in ["yaml", "json"]:
+                        format = ext
+                    else:
+                        format = "json"
+        result = {"format": format, "target": target, "config": dict(values)}
+
+        return result
+
+
+def pretty_print_arrow_table(
+    table: Table,
+    rows_head: typing.Optional[int] = None,
+    rows_tail: typing.Optional[int] = None,
+    max_row_height: typing.Optional[int] = None,
+    max_cell_length: typing.Optional[int] = None,
+) -> RenderableType:
+
+    rich_table = RichTable(box=box.SIMPLE)
+    for cn in table.column_names:
+        rich_table.add_column(cn)
+
+    num_split_rows = 1
+
+    if rows_head is not None:
+
+        if rows_head < 0:
+            rows_head = 0
+
+        if rows_head > table.num_rows:
+            rows_head = table.num_rows
+            rows_tail = None
+            num_split_rows = 0
+
+        if rows_tail is not None:
+            if rows_head + rows_tail >= table.num_rows:  # type: ignore
+                rows_head = table.num_rows
+                rows_tail = None
+                num_split_rows = 0
+    else:
+        num_split_rows = 0
+
+    if rows_head is not None:
+        head = table.slice(0, rows_head)
+        num_rows = rows_head
+    else:
+        head = table
+        num_rows = table.num_rows
+
+    table_dict = head.to_pydict()
+    for i in range(0, num_rows):
+        row = []
+        for cn in table.column_names:
+            cell = table_dict[cn][i]
+            cell_str = str(cell)
+            if max_row_height and max_row_height > 0 and "\n" in cell_str:
+                lines = cell_str.split("\n")
+                if len(lines) > max_row_height:
+                    if max_row_height == 1:
+                        lines = lines[0:1]
+                    else:
+                        half = int(len(lines) / 2)
+                        lines = lines[0:half] + [".."] + lines[-half:]
+                cell_str = "\n".join(lines)
+
+            if max_cell_length and max_cell_length > 0:
+                lines = []
+                for line in cell_str.split("\n"):
+                    if len(line) > max_cell_length:
+                        line = line[0:(max_cell_length)] + " ..."
+                    else:
+                        line = line
+                    lines.append(line)
+                cell_str = "\n".join(lines)
+
+            row.append(cell_str)
+
+        rich_table.add_row(*row)
+
+    if num_split_rows:
+        for i in range(0, num_split_rows):
+            row = []
+            for _ in table.column_names:
+                row.append("...")
+            rich_table.add_row(*row)
+
+    if rows_head:
+        if rows_tail is not None:
+            if rows_tail < 0:
+                rows_tail = 0
+
+            tail = table.slice(table.num_rows - rows_tail)
+            table_dict = tail.to_pydict()
+            for i in range(0, num_rows):
+
+                row = []
+                for cn in table.column_names:
+                    cell = table_dict[cn][i]
+                    cell_str = str(cell)
+
+                    if max_row_height and max_row_height > 0 and "\n" in cell_str:
+                        lines = cell_str.split("\n")
+                        if len(lines) > max_row_height:
+                            if max_row_height == 1:
+                                lines = lines[0:1]
+                            else:
+                                half = int(len(lines) / 2)
+                                lines = lines[0:half] + [".."] + lines[-half:]
+                        cell_str = "\n".join(lines)
+
+                    if max_cell_length and max_cell_length > 0:
+                        lines = []
+                        for line in cell_str.split("\n"):
+
+                            if len(line) > max_cell_length:
+                                line = line[0:(max_cell_length)] + " ..."
+                            else:
+                                line = line
+                            lines.append(line)
+                        cell_str = "\n".join(lines)
+
+                    row.append(cell_str)
+
+                rich_table.add_row(*row)
+
+    return rich_table
diff --git a/src/kiara/utils/pretty_print.py b/src/kiara/utils/pretty_print.py
deleted file mode 100644
index 46557930b..000000000
--- a/src/kiara/utils/pretty_print.py
+++ /dev/null
@@ -1,75 +0,0 @@
-# -*- coding: utf-8 -*-
-import typing
-from pyarrow import Table
-from rich import box
-from rich.console import RenderableType
-from rich.table import Table as RichTable
-
-
-def pretty_print_arrow_table(
-    table: Table,
-    num_head: typing.Optional[int] = None,
-    num_tail: typing.Optional[int] = None,
-) -> RenderableType:
-
-    rich_table = RichTable(box=box.SIMPLE)
-    for cn in table.column_names:
-        rich_table.add_column(cn)
-
-    num_split_rows = 1
-
-    if num_head is not None:
-
-        if num_head < 0:
-            num_head = 0
-
-        if num_head > table.num_rows:
-            num_head = table.num_rows
-            num_tail = None
-            num_split_rows = 0
-
-        if num_tail is not None:
-            if num_head + num_tail >= table.num_rows:  # type: ignore
-                num_head = table.num_rows
-                num_tail = None
-                num_split_rows = 0
-    else:
-        num_split_rows = 0
-
-    if num_head is not None:
-        head = table.slice(0, num_head)
-        num_rows = num_head
-    else:
-        head = table
-        num_rows = table.num_rows
-
-    table_dict = head.to_pydict()
-    for i in range(0, num_rows):
-        row = []
-        for cn in table.column_names:
-            row.append(str(table_dict[cn][i]))
-
-        rich_table.add_row(*row)
-
-    if num_split_rows:
-        for i in range(0, num_split_rows):
-            row = []
-            for _ in table.column_names:
-                row.append("...")
-            rich_table.add_row(*row)
-
-    if num_head:
-        if num_tail is not None:
-            if num_tail < 0:
-                num_tail = 0
-
-            tail = table.slice(table.num_rows - num_tail)
-            table_dict = tail.to_pydict()
-            for i in range(0, num_rows):
-                row = []
-                for cn in table.column_names:
-                    row.append(str(table_dict[cn][i]))
-
-                rich_table.add_row(*row)
-
-    return rich_table
diff --git a/src/kiara/workflow.py b/src/kiara/workflow.py
index b8427f1d1..a321a1f42 100644
--- a/src/kiara/workflow.py
+++ b/src/kiara/workflow.py
@@ -3,6 +3,7 @@
 from rich import box
 from rich.console import Console, ConsoleOptions, RenderResult
 from rich.table import Table
+from slugify import slugify
 
 from kiara.data.values import ValueSet
 from kiara.module_config import KiaraWorkflowConfig
@@ -45,7 +46,9 @@ def __init__(
                 "steps": [
                     {
                         "module_type": self._workflow_config.module_type,
-                        "step_id": self._workflow_config.module_type,
+                        "step_id": slugify(
+                            self._workflow_config.module_type, separator="_"
+                        ),
                         "module_config": self._workflow_config.module_config,
                     }
                 ],