Advancing foundational frameworks for trusted state exchange.
Trusted Frameworks for Digital Interoperability and Industrial Data Quality
Bita Trust develops foundational frameworks and protocol-neutral reference architectures for trusted industrial data and cross-domain interoperability. Grounded in Data Physics, our work examines how trust is formed at source, how the states of physical entities are represented and verified, and how trusted information can be exchanged across systems, organizations and jurisdictions. Our approach is standards-aligned without depending on any single protocol, platform or deployment model.
The Data Physics Trilogy
Industrial information may be understood through states, state evolution and state-derived representations associated with physical entities. For dynamic industrial contexts, State Derivatives (D = dS/dt) provide a way to describe how physical states evolve over time.
The General Theory of Data Physics: A First-Principles Framework for Global Industrial Interoperability
The General Theory of Data Physics: For Industrial Assetization and Cross-Domain Interoperability
The General Theory of Data Physics: For Non-Dependent Data, AI Cognition, and Quantum Anchoring
From Data Physics to Trust at Source and GTSE
Bita Trust develops a layered knowledge architecture for trusted industrial data.
Data Physics provides the first-principles foundation for understanding industrial data through states, state evolution and state-derived representations.
Trust at Source examines how product data becomes trustworthy before external handover, focusing on product reality, observation, facts, evidence, responsibility, boundaries and trusted expression.
Global Trade State Exchange (GTSE) builds on this foundation by exploring how trusted state representations can be exchanged across organizations, platforms, jurisdictions and trust domains without requiring unnecessary transfer of high-resolution source-side data.
The core models may be mapped into independently governed application domains, including DPP, battery, carbon, sustainability and industrial-data use cases. These application domains are not part of the Bita Trust core model and retain their own regulatory, semantic and operational governance.
Trust at Source Framework
A framework for understanding how product data becomes trustworthy at the source before external handover.
Global Trade State Exchange (GTSE) Framework
International Interoperability References
Trust boundaries often exist between supply chain visibility requirements and local data protection considerations. Data Physics introduces a D = dS/dt framework for trusted cross-domain information exchange. The approach supports interoperability across connected ecosystems while preserving local data governance requirements.
Source Ecosystem
Regulatory Framework
- China Data Security Law
- China Cybersecurity Law
- Provisions on Promoting and Regulating Cross-border Data Flows
Standardization Framework
- GB/T 43697-2024
- GB/T 32150-2015
Destination Ecosystem
Regulatory Framework
- Regulation (EU) 2023/2854 (Data Act)
- Regulation (EU) 2024/1781 (Ecodesign for Sustainable Products Regulation – ESPR)
- Regulation (EU) 2023/1542 (Batteries Regulation）
- Carbon Border Adjustment Mechanism (CBAM – EU Regulation 2023/956)
Standardization Framework
- EN 18216
- EN 18219
- EN 18220
- EN 18221
- EN 18222
- EN 18223
- EN 18239
- EN 18246
International Interoperability Frameworks
UN/CEFACT and Related Interoperability References
- United Nations Transparency Protocol (UNTP)
- Supply Chain Reference Data Model (SCRDM)
- Verifiable Credentials and Cross-Mapping Concepts
ISO Global Standards
- ISO 14067 — Carbon footprint of products
- ISO 14040 / ISO 14044 — Life cycle assessment
- ISO 8000 — Data quality
- ISO/IEC 27001 — Information security management
Architectural Principles
These principles are informed by the research foundations of the General Theory of Data Physics. The framework explores how industrial information can be represented through dynamic State Derivatives (D = dS/dt) associated with physical entities. By separating physical characteristics from contextual requirements, the architecture enables trusted information exchange and supports interoperability across heterogeneous domains.
Ontological Orthogonality & State-Attribute Decoupling
Architecturally decoupling Physical Characteristics (Intrinsic State Vectors) from Context-Dependent Social Constructs (Extrinsic Context Layers). Enabling physical characteristics to be interpreted across ecosystems while contextual requirements remain locally governed.
The Mechanics of State Coupling
Strictly distinguishing the systemic mechanics between decoupled digital attributes used in reporting, sustainability accounting or financial assessment contexts.
The Temporal Continuity Principle
Where dynamic state data is relevant, digital trust may be strengthened by continuous and verifiable information flows. Complementing traditional reports with continuous state representations helps maintain alignment between digital records and physical assets throughout their lifecycle.
Building trusted digital ecosystems through research and engineering principles inspired by the rigor of physics.
In digital ecosystems, trust can be strengthened through verifiable information architectures and interoperable exchange mechanisms. We welcome collaboration with industry, academia, standards communities and technology practitioners to advance trusted digital interoperability together.
