{
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   "source": [
    "# Exploring the Ontology with EMMOntoPy\n",
    "\n",
    "This notebook shows how to use **EMMOntoPy**, a Python interface for OWL ontologies based on EMMO, to retrieve structured information from the `domain-battery` ontology.\n",
    "\n",
    "EMMOntoPy makes it simple to:\n",
    "\n",
    "- Retrieve ontology classes and properties by label\n",
    "- Access rich metadata (like `elucidation`, `IEVReference`)\n",
    "- Integrate semantic battery data into other tools or pipelines\n",
    "\n",
    "Let's explore the `BatteryCell` class from the battery ontology.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "dbeb9508",
   "metadata": {},
   "outputs": [],
   "source": [
    "from ontopy import get_ontology\n",
    "\n",
    "# Loading from web\n",
    "battinfo = get_ontology('https://w3id.org/emmo/domain/battery/inferred').load()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bcd538ce",
   "metadata": {},
   "source": [
    "## Access a Class from the Ontology\n",
    "\n",
    "We start by retrieving the `BatteryCell` class from the ontology. Each class has a globally unique identifier (IRI) and carries metadata that helps us understand its role in the ontology.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "984ff91e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "IRI: https://w3id.org/emmo/domain/battery#battery_68ed592a_7924_45d0_a108_94d6275d57f0\n"
     ]
    }
   ],
   "source": [
    "battery = battinfo.BatteryCell\n",
    "\n",
    "# Print its IRI (unique identifier in the ontology)\n",
    "print(\"IRI:\", battery.iri)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b7af25ac",
   "metadata": {},
   "source": [
    "## View Properties Associated with the Class\n",
    "\n",
    "We can retrieve the object and data properties that are defined for this class using `.get_class_properties()`. These properties describe the relationships and attributes a `BatteryCell` can have."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "bf28dd9e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Class Properties:\n",
      " - core.altLabel\n",
      " - emmo.IEVReference\n",
      " - emmo.elucidation\n",
      " - core.prefLabel\n"
     ]
    }
   ],
   "source": [
    "# Retrieve all properties (object & data) where BatteryCell is in the domain\n",
    "print(\"Class Properties:\")\n",
    "for p in battery.get_class_properties():\n",
    "    print(f\" - {p}\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6772ae1e",
   "metadata": {},
   "source": [
    "## View Annotations Like Elucidation and Standards References\n",
    "\n",
    "Ontology classes often carry rich semantic annotations such as `elucidation` (a human-readable explanation) or `IEVReference` (a standards reference, e.g. from IEC). These are useful for interoperability and traceability."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "21e2187b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Elucidation: [locstr('basic functional unit, consisting of an assembly of electrodes, electrolyte, container, terminals and usually separators, that is a source of electric energy obtained by direct conversion of chemical energy.', 'en')]\n",
      "IEV Reference: ['https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=482-01-01']\n"
     ]
    }
   ],
   "source": [
    "# Print annotation properties\n",
    "print(\"Elucidation:\", battery.elucidation)\n",
    "print(\"IEV Reference:\", battery.IEVReference)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0d31d4eb",
   "metadata": {},
   "source": [
    "## Explore the Class Hierarchy\n",
    "\n",
    "The `.is_a` attribute shows the direct superclass(es) of the class, while `.mro()` (method resolution order) lists the full inheritance chain from the most specific to the most general.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "8a968869",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Immediate superclasses (is_a): [battery.Battery, electrochemistry.ElectrochemicalDevice]\n",
      "Full inheritance chain (MRO):\n",
      " - battery.BatteryCell\n",
      " - battery.Battery\n",
      " - electrochemistry.ElectrochemicalDevice\n",
      " - emmo.Device\n",
      " - emmo.ManufacturedProduct\n",
      " - emmo.Product\n",
      " - emmo.Maximal\n",
      " - emmo.Fundamental\n",
      " - emmo.Structural\n",
      " - electrochemistry.ElectrochemicalCell\n",
      " - emmo.HolisticArrangement\n",
      " - emmo.HolisticSystem\n",
      " - emmo.Whole\n",
      " - emmo.QualifiedWhole\n",
      " - emmo.Holistic\n",
      " - emmo.Object\n",
      " - emmo.Persistence\n",
      " - emmo.Perspective\n",
      " - emmo.CausalStructure\n",
      " - emmo.Fusion\n",
      " - emmo.Item\n",
      " - emmo.EMMO\n",
      " - owl.Thing\n",
      " - <class 'object'>\n"
     ]
    }
   ],
   "source": [
    "# Show the direct superclass(es)\n",
    "print(\"Immediate superclasses (is_a):\", battery.is_a)\n",
    "\n",
    "# Show the method resolution order (full class inheritance chain)\n",
    "print(\"Full inheritance chain (MRO):\")\n",
    "for cls in battery.mro():\n",
    "    print(f\" - {cls}\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4c1dd26e",
   "metadata": {},
   "source": [
    "## Summary\n",
    "\n",
    "EMMOntoPy allows you to access structured ontology knowledge in Python with minimal effort:\n",
    "\n",
    "- Use `.iri`, `.is_a`, and `.elucidation` for metadata\n",
    "- Use `.get_class_properties()` to integrate ontology structure with simulation tools, ELNs, or data pipelines\n",
    "\n",
    "Next steps:\n",
    "- Build instances of `BatteryCell` using JSON-LD or RDF\n",
    "- Annotate test data using ontology terms\n",
    "- Query the ontology with SPARQL or integrate into a digital twin\n",
    "\n"
   ]
  }
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