enrich-ontology

name: enrich-ontology description: Map a Cartography node into the Ontology system using semantic labels (UserAccount, DeviceInstance, Tenant, Database, ObjectStorage, FileStorage) or canonical nodes (User, Device). Use when the user asks to add ontology mapping, expose a node as a semantic label, normalise identity / device data across providers, enable cross-module queries, or wire _ont_* properties.

enrich-ontology

Cartography's Ontology system unifies data from multiple sources via two mechanisms:

1. Semantic labels (recommended) — adds labels (e.g. UserAccount) and prefixed properties (_ont_*) directly to source nodes during ingestion.
2. Canonical nodes — separate (:User:Ontology) / (:Device:Ontology) nodes that aggregate data from multiple sources.

Most modules only need semantic labels.

Critical rules

1. Mark primary identifiers required=True in OntologyFieldMapping (e.g. email for User, hostname for Device). Records missing these are excluded from ontology node creation.
2. For semantic labels, just add ExtraNodeLabels(["UserAccount"]) to your node schema. The ontology system handles the _ont_* properties automatically.
3. special_handling values are strings: invert_boolean, to_boolean, or_boolean, nor_boolean, equal_boolean, static_value, coalesce. Boolean conditions inside extra={"values": ...} must also be strings ("true", not True).
4. Document ontology mapping in your schema doc using the standard blockquote phrase.
5. Module name microsoft is the canonical source for Microsoft Graph. entra is still accepted as a backward-compatible alias during migration.

Instructions

Step 1 — Decide: semantic label or canonical node?

When in doubt, start with semantic label.

Step 2 — Author the mapping

Add the mapping in cartography/models/ontology/mapping/data/. For users:

# cartography/models/ontology/mapping/data/useraccounts.py
from cartography.models.ontology.mapping.specs import (
    OntologyFieldMapping, OntologyMapping, OntologyNodeMapping,
)


your_service_mapping = OntologyMapping(
    module_name="your_service",
    nodes=[
        OntologyNodeMapping(
            node_label="YourServiceUser",
            fields=[
                OntologyFieldMapping(ontology_field="email",     node_field="email", required=True),
                OntologyFieldMapping(ontology_field="username",  node_field="username"),
                OntologyFieldMapping(ontology_field="fullname",  node_field="display_name"),
                OntologyFieldMapping(ontology_field="firstname", node_field="first_name"),
                OntologyFieldMapping(ontology_field="lastname",  node_field="last_name"),

                OntologyFieldMapping(
                    ontology_field="inactive",
                    node_field="account_enabled",
                    special_handling="invert_boolean",
                ),
                OntologyFieldMapping(
                    ontology_field="has_mfa",
                    node_field="multifactor",
                    special_handling="to_boolean",
                ),
                OntologyFieldMapping(
                    ontology_field="inactive",
                    node_field="suspended",
                    special_handling="or_boolean",
                    extra={"fields": ["archived"]},
                ),
            ],
        ),
    ],
)

For devices the pattern is the same with OntologyNodeMapping(node_label="YourServiceDevice", ...).

Step 3 — Register the mapping

Add it to the dictionary at the bottom of the file:

# Example: bottom of useraccounts.py
USERACCOUNTS_ONTOLOGY_MAPPING: dict[str, OntologyMapping] = {
    # ... existing mappings ...
    "your_service": your_service_mapping,
}

The mappings are auto-imported via cartography/models/ontology/mapping/__init__.py.

Step 4 — Wire the semantic label on your node schema

For semantic labels, the node schema simply gains the extra label — Cartography injects _ont_* and _ont_source automatically at ingestion:

from cartography.models.core.nodes import ExtraNodeLabels


@dataclass(frozen=True)
class YourServiceUserSchema(CartographyNodeSchema):
    label: str = "YourServiceUser"
    extra_node_labels: ExtraNodeLabels = ExtraNodeLabels(["UserAccount"])
    properties: YourServiceUserNodeProperties = YourServiceUserNodeProperties()
    sub_resource_relationship: YourServiceTenantToUserRel = YourServiceTenantToUserRel()

For canonical nodes, define a separate schema with extra_node_labels=ExtraNodeLabels(["Ontology"]) and a relationship to the semantic-labelled source nodes. See references/semantic-labels.md for the full template.

Step 5 — required and eligible_for_source

required=True means: source records lacking this field are excluded from ontology node creation. Always mark the primary identifier required:

OntologyFieldMapping(ontology_field="email",    node_field="email",       required=True)
OntologyFieldMapping(ontology_field="hostname", node_field="device_name", required=True)

OntologyNodeMapping.eligible_for_source=False means: this mapping links existing ontology nodes but cannot create new ones. Use it when the source lacks the required identifier:

# AWS IAM users have no email, so they cannot create new User ontology nodes.
OntologyNodeMapping(
    node_label="AWSUser",
    eligible_for_source=False,
    fields=[
        OntologyFieldMapping(ontology_field="username", node_field="name"),
    ],
),

Step 6 — Cross-entity relationships (e.g. user owns device)

For services that link users to devices, add a statement to the appropriate ontology analysis JSON file (e.g. cartography/data/jobs/analysis/ontology_devices_linking.json):

{
  "__comment": "Connect users to their devices via YourService",
  "query": "MATCH (u:User)-[:HAS_ACCOUNT]->(:YourServiceUser)-[:OWNS]->(:YourServiceDevice)<-[:OBSERVED_AS]-(d:Device) MERGE (u)-[r:OWNS]->(d) ON CREATE SET r.firstseen = timestamp() SET r.lastupdated = $UPDATE_TAG",
  "iterative": false
}

See the analysis-jobs skill for the JSON job format.

Step 7 — Test

For semantic labels — assert _ont_* properties land on your nodes:

def test_ontology_properties(neo4j_session):
    # after running your sync
    row = neo4j_session.run(
        "MATCH (n:YourServiceUser) RETURN n._ont_email, n._ont_source LIMIT 1"
    ).single()
    assert row["n._ont_email"] is not None
    assert row["n._ont_source"] == "your_service"

For canonical nodes — assert the ontology intel module produces them:

def test_canonical_user_created(neo4j_session):
    row = neo4j_session.run(
        """
        MATCH (u:User:Ontology)-[:HAS_ACCOUNT]->(ua:YourServiceUser)
        RETURN count(u) AS user_count
        """
    ).single()
    assert row["user_count"] > 0

Step 8 — Document the integration

In docs/root/modules/your_service/schema.md, add the standard blockquote phrase under the node title:

### YourServiceUser

Represents a user in Your Service.

> **Ontology Mapping**: This node has the extra label `UserAccount` to enable cross-platform queries for user accounts across different systems (e.g., OktaUser, EntraUser, GSuiteUser).

Standard phrases by semantic label:

special_handling quick reference

Canonical node configuration (CLI)

cartography --ontology-users-source "okta,microsoft,gsuite"
cartography --ontology-devices-source "crowdstrike,kandji,duo"

References (load on demand)

• references/semantic-labels.md — execution flow, available labels/fields, full canonical-node schema example, eligible_for_source deep dive.