Event Data
Event data and master data are core concepts of traceability. The frameworks described in this knowledge base build on top of the EPCIS 2.0 definitions for these concepts. Event data describes things…
Event data and master data are core concepts of traceability. The frameworks described in this knowledge base build on top of the EPCIS 2.0 definitions for these concepts.
Event data describes things that happen to product instances at specific moments in time. An example might include, "At 1:23 pm on 15 March 2004, Product A was shipped to Location B." Master data gives context to the event data by providing details about product A and Location B.
Product A:
- Name: 12oz Rib Eye Steak
- GTIN: urn:gdst:example.org:product:class:example_prefix.A
Location B:
- Name: Beef Distributor Warehouse B
- Street Address: 123, Warehouse B, Houston, Texas, 77065
Understanding Events
Event data is composed of individual events.
An event is:
- A record that associates EPCs with a moment in time (
eventTime). - Structured based on one of the five canonical Event Types
ObjectEventAggregationEventAssociationEventTransformationEventTransactionEvent
- Immutable after successful submission, ensuring integrity and an audit trail.
Event Data serves as the primary data source for answering three classes of visibility queries:
- Where is it?
- What is its history?
- What happened to it?
Event Structure and Composition
Core Composition of a Traceability Event
Component | Nomenclature | Data Type / Nature | Purpose within Event Data |
Event Type |
| Qualified Name (URI) | Determines the schema and the nature of the captured action. It is the structure classifier. |
Event Fields |
| Primitive Types ( | Named fields that populate the contextual details (When, Where, Why, Who/What). |
Event Identifier |
| URI (gs1:EventID) | A cryptographically strong identifier to track the individual event. Vital for deduplication and referencing. |
User Extensions | N/A | User-defined Types (Custom Namespace) | Allows proprietary, business-specific data to be encapsulated within the event without violating core EPCIS interoperability. |
Event Data vs Master Data
The separation between Event Data and Master Data is architecturally central to EPCIS and is based on three key vectors: Time, Content, and Mutability.
Technical and Functional Differentiation
Characteristic | Event Data (Transaction Facts) | Master Data (Reference Data) |
Temporal Volatility | High: Capture of point-in-time events, resulting in high record volume. - Example: Recording 300 | Low: Descriptive attribute that changes slowly or rarely. - Example: The name or description of the product ( |
Mutability (Design Principle) | Immutable (Append-only): Event Data is a historical record. Corrections require submitting a new voiding/replacing event. - Example: If the | Mutable: Can be updated (e.g., change in a |
Semantic Function | Occurrence ( | Context ( |
Identifier Usage | Usage Source: Contains resolvable references (URIs) to entities. - Example: The | Definition Source: Defines and stores the attribute associated with those identifiers. - Example: The Master Data system stores: |
Additional Resources
The Traceability Framework Implementation Guide
The following documents constitute the primary mapping resource, applying EPCIS directly to the business processes:
- Global Traceability Frameworks for Beef & Leather: This is the overarching document. It sets the high-level context and the Framework Requirements, defining which data (Data Collection) is necessary for the Event Data.
- Critical Tracking Events (CTEs): This group of articles forms the basis of the mapping. These articles define the Event Types that are mandatory for each step in the value chain:
- Example Event Mapping (Transformation Event, Shipping Event, etc.): These articles detail the one-to-one mapping. They instruct, for instance, which specific
bizStepanddispositionmust be used when a Receiving Event or Shipping Event occurs in the project. - Cattle Birthing: This is a crucial CTE that instructs the creation of the first Traceability Event, establishing the animal´s origin (
sourceList).
- Example Event Mapping (Transformation Event, Shipping Event, etc.): These articles detail the one-to-one mapping. They instruct, for instance, which specific
Identification and Context Resources
Mapping the Event Data is incomplete without the rules defining how identifiers (EPCs) and contextual data (Master Data) must be structured.
- GFTBL Identifiers: This article is vital. It defines the encoding rules for transforming the internal IDs (for animals, cases, locations) into the required EPC URIs and SGLN URIs used in the
epcListandbizLocationfields of the Event Data. - Master Data Mapping: This article acts as the contextual resource. It outlines the Master Data attributes (such as the full legal name of a farm) that are referenced by, but not stored in, the Event Data.
- JSON Schemas: This technical resource defines the exact syntax and data structure to ensure the Traceability Events generated are compliant and acceptable to data exchange systems (Data Exchange).
How did we do?
Master Data
Identifiers