Resources & Research

Explore our collection of background materials, research papers, and interactive visualizations that explain the concepts and technologies behind the Semantic Data Charter™.

Featured: Interactive Infographic

Interactive Last updated: July 2024

Neuro-Symbolic AI & Semantic Data Charter™

An interactive infographic exploring the convergence of Neuro-Symbolic AI and the Semantic Data Charter™. This comprehensive visualization demonstrates how these two transformative technologies work together to create explainable, robust, and trustworthy artificial intelligence systems.

What you'll learn: The fundamental differences between neural networks and symbolic AI, how they complement each other, key research institutions advancing the field, and the critical role that semantic data governance plays in enabling truly intelligent systems.

Research Papers & Reports

Published Paper Economic modeling study · 2026 · CC-BY

Substrate Economics: The Token-Cost Asymmetry Between Deterministic and Inference-Based Governance

Cook, Abby, and Cavalini model the cost difference between two ways to keep data trustworthy: enforcing correctness once with a deterministic substrate (CPU-bound schema and provenance checks) versus re-checking it with LLM inference on every read (inference-bound). Enforcing it at the substrate is orders of magnitude cheaper at scale.

Why it matters: governance cost is usually treated as a fixed tax; the paper shows it is a design choice. In the sensitivity analysis, even a 90% collapse in open-source token prices leaves the deterministic-governance advantage intact by five to six orders of magnitude. This is an economic modeling study, not a telemetry benchmark.

DOI: 10.5281/zenodo.20679739

Published Paper Joint technical note · Cook and Abby · OSF

MTCP × SDC Integration

A joint technical note with Ahmad Abby, creator of the Model Trust Capability Profile (MTCP), documenting how an action-layer model-evaluation framework composes with the SDC substrate. MTCP measures whether an LLM actually holds its constraints under sustained pressure; SDC binds governance state to the data itself. The paper shows the two layers working together: an MTCP Evidence Pack consumed as an SDC-governable artifact, feeding governance decisions backed by hash-chained, reproducible receipts.

Why it matters: it is a worked, reproducible example of substrate-and-monitor cooperation. Two independent failure findings, surfaced by two researchers, converge on one point: constraint discipline does not track model size, so correctness has to be enforced at the substrate and verified at the action layer, not assumed from the model.

Discussion Input W3C Context Graphs CG

SDC and the Context Graph Four Facets

A bind-at-source mapping of SDC onto the Context Graph Protocol's four facets: Data, Meaning, Structure and World. CGP measures whether a boundary crossing's facets are LIT or DARK; SDC binds Meaning, Structure and World at authoring time so they arrive LIT. Includes a Form 1040 standard-deduction example, the SHACL adapter path, and a proposed three-arm benchmark contribution for the group's tax-preparation white paper.

Four Facets Dark Fraction Bind at Source
PDF Research Report

Neuro-Symbolic AI and Semantic Data Charter: A Pathway to Explainable AI

This comprehensive research paper examines the technical foundations and practical applications of combining Neuro-Symbolic AI with the Semantic Data Charter™ framework. The document explores how integrating symbolic reasoning with neural learning creates AI systems that are not only powerful but also transparent and verifiable.

Key topics covered: The paradigm shift from pure neural networks to hybrid systems, the role of formal data governance in AI trustworthiness, real-world implementation challenges, and future research directions in explainable artificial intelligence.

PDF Technical Paper

Outliers: Noise or Discovery?

A critical examination of how data anomalies and outliers should be treated in modern data systems. This paper challenges the common practice of automatically dismissing outliers as "noise" and presents a framework for determining when exceptional values represent meaningful signals versus data quality issues.

Why it matters: In the context of the Semantic Data Charter™, proper handling of exceptional values is crucial for data integrity. This paper demonstrates how formal governance and semantic validation can help organizations distinguish between genuine insights and data errors, enabling both robust analytics and the preservation of potentially groundbreaking discoveries.

Technical Documentation

Documentation Comprehensive Standards Reference

Standards Compliance Documentation

Complete overview of international standards, specifications, and protocols implemented in SDCStudio and enabled through the SDC4 Reference Model. This comprehensive guide covers W3C, ISO, IETF, and industry standards compliance.

Includes: RDF, OWL, SPARQL, SHACL, XSD schemas, ISO 21090 NULL Flavors, ISO 8601 temporal support, IETF language tags, NIEM patterns, Dublin Core metadata, spatio-temporal tagging, access control standards (HIPAA, GDPR, NIST), and complete standards reference matrix.

Technical Reference SDC4 Schema Documentation

XSD Schema Documentation

Detailed technical documentation for the SDC4 (Semantic Data Charter Release 4.0) XSD schema. Browse the complete reference for all data types, elements, complex types, and simple types with their properties, constraints, and relationships.

Coverage includes: XdString, XdBoolean, XdQuantity, XdTemporal, XdFile, Cluster, Item, Audit, Attestation, Participation types, 15 ExceptionalValue types, list types, interval types, and all SDC4 reference model components with complete inheritance hierarchies.

Healthcare 3 Comprehensive Guides

FHIR Integration Guides

Complete technical documentation for integrating HL7 FHIR R4 with SDC4. Includes datatype analysis, holistic mapping guide, and quick reference decision matrix.

Datatypes Analysis Mapping Guide Decision Matrix
Government 7 Strategic Documents

NIEM Integration Guides

Strategic analysis and technical documentation for NIEM → SDC4 migration. Covers architecture overview, semantic challenges, government-wide vision, person mapping, cross-domain reuse, core concepts, and quick reference.

Overview Semantic Analysis Person Mapping +4 more
Business Analysis and demonstration

Business Data Exchange

Orders, ship notices, invoices and remittances as Governed Data Records composed from open standards, with the partner's mandated format a projection of the record. Where the recurring cost of B2B integration lives today, and the demonstration scheduled for the first quarter of 2027.

Where the cost lives The Governed Data Record Halvorsen demonstration
Settlement Available now

Verifiable Settlement Integration Guides

How exchanged business documents settle on the Verifiable Settlement Layer: each exchange validated against its published model, the transition authorized by governance, and a receipt both parties can verify.

Documents to Settlement Data Layer Vision

Community Contributions

Independent analyses and knowledge graphs created by the community under Creative Commons licensing.

Community CC BY 4.0

Unbaking the Cake — Capturing Data Before Entropy

Data is born structured. The GenAI industry spends billions trying to reverse-engineer structure from documents. The solution isn't better RAG — it's better capture at the source. Includes infographic, slide deck, semantic knowledge graph, and Neo4j import.

Content by Dinis Cruz · Based on post by Timothy Cook

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Community CC BY 4.0

Data Physics — The Semantic Capture of Intent

The “Data Management” era is over. Three metaphors frame the SDC approach: The Cake (entropy prevention), The Prism (value refraction into Dev/Legal/AI), and The Fortress (500 endpoints collapsed to 2 gates). Full knowledge graph with Neo4j import.

Content by Dinis Cruz · Based on post by Timothy Cook

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