Open Data Infrastructure for Logistics and Supply Chain

Supply chain visibility sounds simple until the data has to cross a company boundary.

Supply chain visibility is a data contract problem

Logistics data looks operational, but the hard part is trust. A purchase order becomes a shipment. A shipment becomes a container. A container becomes a handoff across carriers, warehouses, ports, customs processes, and customers. Every handoff creates data that someone else needs to use.

If that information lives inside one platform, supply chain visibility becomes a screenshot economy. Teams can see what the portal shows them, but they cannot reliably join events with planning data, quality signals, inventory history, or customer promises without another integration project.

Events matter more than dashboards

Useful supply chain systems do not just store current state. They capture what happened, when it happened, where it happened, why it happened, and which asset or product was involved. GS1 EPCIS and CBV exist because supply chains need a common language for visibility events across trading partners.

That maps cleanly to ODI. An event standard gives partners a shared event shape. Open data infrastructure gives the enterprise a way to store, govern, query, and explain those events alongside the rest of the business. The standard is the vocabulary. ODI is the operating model that keeps the vocabulary usable.

The architecture has to preserve partner meaning

A practical ODI supply chain architecture separates four concerns:

• event capture: shipment, location, condition, chain-of-custody, and exception events
• identity: product, location, organization, asset, and partner identifiers
• open tables: durable analytical history in formats that multiple engines can read
• governance: partner-specific access, retention, consent, audit, and provenance

The failure mode is to collapse all four into one application. That may work for the first visibility use case. It breaks when finance, operations, customer experience, and AI systems need the same events for different reasons.

AI raises the cost of bad traceability

Agents and copilots will not make supply chain data easier to govern. They will make weak governance more visible. If an agent recommends expediting a shipment, it needs to know which events are current, which partner supplied them, which confidence signals exist, and which data it is allowed to expose.

This is where verifiable credentials, lineage, and open table contracts start to matter. The point is not to turn every supply chain into a blockchain demo. The point is to make claims about movement, custody, certification, temperature, or delay traceable enough that software can use them without guessing.

A supply chain ODI checklist

Use these questions before calling a logistics data platform open:

• Can partners exchange event data through documented standards or APIs?
• Can the enterprise store event history in open tables outside the visibility application?
• Can identifiers for products, locations, assets, and partners be resolved consistently?
• Can access rules differ by partner, lane, product, and purpose?
• Can lineage show which partner, system, or device created a decision-critical event?

If the answer is no, the organization does not have visibility yet. It has a screen with some supply chain data on it.

Sources to start with

Start with standards that define shared event language, then treat ODI as the analytical and governance layer around those events.

• GS1 EPCIS and CBV standards
• W3C Verifiable Credentials Data Model
• OpenLineage documentation
• Apache Iceberg table specification