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Architecture Overview

Graphical Representation

DPP & DMP Architecture

Three-Group Architecture Structure

The CE-RISE DPP & DMP architecture is organized into three main groups containing 9 functional layers, where each group and layer serves specific purposes while maintaining interoperability across the system.

A. Core Layers

The core layers form the foundation of every Digital Product or Material Passport, providing essential identity and metadata management infrastructure.

A1. Passport Identification

Models:

product-profile (required for product passports)
Defines the immutable identity, origin, and basic specification of the product. This foundational model is static and always present in every product DPP.

material-profile (required for material passports)
Defines the immutable identity, origin, and basic specification of the material. This foundational model is static and always present in every material DMP.

A2. DPP & DMP Metadata

Models:

dp-record-metadata
Defines the semantic and structural metadata of the DPP or DMP record. Specifies the applied data models, profiles, ontology bindings, schema references, supported formats, validation schemas, and version information required for interpreting the content of the DPP or DMP. This is the primary metadata envelope read before processing any product or material data.

dp-access-and-governance
Describes operational and access-related metadata for the DPP or DMP record. Defines access levels, security settings, data carrier characteristics, longevity policies, interoperability configurations, and other parameters governing how the DPP or DMP is stored, exposed, shared, and maintained across systems.

dp-record-custody
Represents the chain of custody and governance history of the DPP or DMP record itself. Captures custody events (creation, update, transfer, archival), identifies custodians, records authorized transfers, and includes integrity evidence such as signatures or hashes. Ensures auditability, accountability, and secure lifecycle governance of the DPP or DMP as an information object.

B. Value-Added Information Layers

These layers provide the rich, domain-specific information that creates value for different stakeholders throughout the product or material lifecycle.

B1. Dynamic Lifecycle

Captures time-dependent changes and events throughout the product's journey.

Models:

traceability-and-lifecycle-events
Dynamic traceability and supply-chain events. Includes only events, not static identifiers.

diagnostic-results
Structured outputs produced during diagnostic, repair, service, or automated condition-assessment operations. These are event-bound results, not static product information.

B2. Operation & Use

Describes how a product or material is used, maintained, and operated throughout its active life.

Model: usage-and-maintenance Captures how a product is operated and maintained, including usage records, maintenance actions, service histories, and legally required or product-specific instructions for use and upkeep.

B3. Impact Assessment

Supports comprehensive environmental, social, and economic impact calculations.

Models:

integrated-lca
Represents integrated LCA results, including environmental, social, and economic impact indicators, methodological metadata, calculation parameters, characterization choices, and assessment settings.

assessed-system
The underlying assessed-system data model used to structure activities, flows, and elementary exchanges for products, materials, components, or assemblies.

B4. Circularity & End-of-Life

Defines circularity metrics, design principles, and end-of-life pathways.

Models:

circularity-and-eol
Comprehensive circularity and end-of-life information.

re-indicators-specification
Specific end-of-life indicators and recovery options for selected products.

Ensures regulatory compliance and standards conformity throughout the product lifecycle.

Models:

compliance-and-standards
Regulatory compliance and certification information.

conformity-requirements-specification
Specification layer for compliance and normative information needs.

C. Cross-Cutting Utility Layers

These layers provide reusable components that support data quality and reliability across all other layers.

C1. Uncertainty

Model: uncertainty-quantification
Generic structures for representing uncertainty in measurements, assessments, and indicators.

Used by: All layers where measurements, predictions, or assessments contain uncertainty

C2. Data Quality

Model: data-quality-framework
Defines metadata for data quality, provenance, representativeness, completeness, and assessment pedigree.

Used by: All layers to ensure transparency and trust in data

Architecture Principles

Modularity

Each model can be developed, updated, and deployed independently while maintaining interface compatibility.

Interoperability

Models use standardized interfaces and semantic definitions to ensure seamless integration across different systems and platforms.

Extensibility

The architecture allows for new models to be added within existing layers or new layers to be created as requirements evolve.

Separation of Concerns

Each layer addresses distinct aspects of the product or material lifecycle, preventing unnecessary coupling and enabling focused expertise.

For detailed specifications and internal structure of each model, see the individual component repositories.