Supply Chain Semantic Ontology Layer¶

The Semantic Ontology Layer sits between the Data Plane and the Application Catalogue, providing a unified, standards-aligned knowledge graph that resolves entities across Salesforce CRM, SAP S/4HANA, Oracle ERP (Finance & Operations), and unstructured data sources.

Industry Standards Alignment¶

The supply chain ontology is aligned to two global standards — the equivalent of TMF Open APIs used in the Telco vertical.

SCOR (Supply Chain Operations Reference)¶

The ASCM/APICS SCOR model is the global standard for supply chain management. Every domain, workflow, and policy in this ontology is tagged with its SCOR process:

SCOR Process	Scope	Ontology Coverage
Plan	Demand forecasting, S&OP, inventory planning	Demand Forecasting app, Inventory Optimization app
Source	Procurement, vendor management, receiving	Procurement Analytics app, Supply Chain Risk app
Make	Production scheduling, manufacturing, quality	Production & Quality app
Deliver	Order fulfillment, warehousing, transportation	Order-to-Cash app, Customer 360 app
Return	Reverse logistics, defective/excess handling	Return_Order entity, Expiry Management workflow
Enable	Governance, master data, compliance, sustainability	ESG app, all policies, master data domains

GS1 Standards¶

Product identification and traceability entities carry GS1-aligned identifiers:

GS1 Standard	Purpose	Ontology Entity
GTIN (Global Trade Item Number)	SKU identification	`Material_Master.GTIN`
GLN (Global Location Number)	Warehouse/plant location	`Plant_Master.GLN`
SSCC (Serial Shipping Container Code)	Shipment tracking	`Delivery_Document.SSCC`
Batch/Lot	Traceability and recall	`Batch_Master.Batch_ID`

Architecture¶

graph TD
    subgraph DataPlane [Data Plane - 6 Source Systems]
        SF["Salesforce CRM"]
        SAP["SAP S/4HANA"]
        ORA["Oracle ERP"]
        GD["Google Drive"]
        FU["File Uploads"]
        SL["Social Listening"]
    end

    subgraph OntologyLayer [Semantic Ontology Layer]
        SCHEMA["Schema<br/><i>12 Domains · ~45 Tables</i>"]
        WF["Workflows<br/><i>12 SCOR-aligned</i>"]
        POL["Policies<br/><i>8 Governance Rules</i>"]
        INT["Integrations<br/><i>6 System Mappings</i>"]
    end

    subgraph Apps [Application Catalogue - 8 Apps]
        DF["Demand Forecasting"]
        IO["Inventory Optimization"]
        O2C["Order-to-Cash"]
        SCR["Supply Chain Risk"]
        C360["Customer 360"]
        PA["Procurement Analytics"]
        PQ["Production & Quality"]
        ESG["ESG Tracker"]
    end

    SF --> SCHEMA
    SAP --> SCHEMA
    ORA --> SCHEMA
    GD --> SCHEMA
    FU --> SCHEMA
    SL --> SCHEMA

    SCHEMA --> WF
    POL --> WF
    INT --> SCHEMA

    WF --> DF
    WF --> IO
    WF --> O2C
    WF --> SCR
    WF --> C360
    WF --> PA
    WF --> PQ
    WF --> ESG

Ontology Components¶

The ontology consists of four interconnected layers, all stored in enterprise-knowledge/:

Layer	Files	Format	Purpose
Schema	`supply-chain-schema.yaml`	YAML	12 domains, ~45 tables with fields, types, risk levels, constraints, and relationships
Workflows	`workflows/*.yaml` (12 files)	YAML	Triggered process flows with steps, rules, SLAs, and dependencies
Policies	`policies/*.md` (8 files)	Markdown	Business rules, thresholds, approval chains, and compliance constraints
Integrations	`integrations/*.yaml` (6 files)	YAML	Field-level sync mappings between source systems with conflict resolution

Relationship Types¶

Entities in the schema are connected via typed relationships that form a knowledge graph:

Relationship	Meaning	Example
`triggers`	Entity event initiates a workflow	`Inventory_Position` triggers `Inventory Rebalancing` workflow
`syncs_to`	Entity data flows to another system	`Account` syncs_to `Oracle_AR_Customer` via integration
`constrained_by`	Entity operations governed by a policy	`Batch_Master` constrained_by `quality-policy`
`depends_on`	Entity requires a parent/related entity	`Opportunity_Line_Item` depends_on `Material_Master`
`validates`	Entity validates another in a business process	`Goods_Receipt` validates `Oracle_AP_Invoice` in three-way match

Cross-Application Entity Heatmap¶

Shows how many of the 8 supply chain apps require each entity. Higher usage = more foundational.

Entity	Count	Applications
`Material_Master`	8	All apps
`Oracle_Cost_Accounting`	4	Inventory, Customer 360, Production, ESG
`Delivery_Document`	4	Inventory, O2C, Customer 360, ESG
`Account`	4	Demand, O2C, Customer 360, Inventory
`Opportunity`	4	Demand, O2C, Customer 360, Inventory
`Plant_Master`	3	Inventory, Production, ESG
`Inventory_Position`	3	Demand, Inventory, Production
`Batch_Master`	2	Inventory, Production
`Vendor_Master`	2	Risk, Procurement
`Oracle_Purchase_Order`	2	Risk, Procurement
`Contract_Document`	2	Risk, Procurement
`Market_Signal`	2	Demand, Risk
`Brand_Sentiment`	2	Customer 360, ESG

Material_Master is the most connected entity in the supply chain ontology — equivalent to Account in CRM or Subscriber in Telco.

Schema Statistics¶

Metric	Count
Domains	12
Tables	~45
Source Systems	6 (Salesforce, SAP, Oracle, Google Drive, File Uploads, Social Listening)
Workflows	12
Policies	8
Integrations	6
Relationship Types	5 (triggers, syncs_to, constrained_by, depends_on, validates)
SCOR Processes Covered	6/6 (Plan, Source, Make, Deliver, Return, Enable)

Documentation¶

Document	Description
Schema Reference	Complete domain and table reference with fields, types, and relationships
Workflows	All 12 AI workflow definitions with triggers, steps, and dependencies
Policies	All 8 governance policies with rules, thresholds, and approval chains
Integrations	All 6 system integration mappings with field-level detail
App-Object Mapping	Minimum required objects per application with relationship matrix

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