PMC — Policy–Metadata Coherence

 The traceability kernel that encodes legal and policy text into machine-readable knowledge, forming the informational backbone of coherence and regulatory intelligence 

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    Making Data Understandable from Within (SDG 17.14)

     

    Public and corporate data often describe outcomes without revealing their origins.
    Indicators show what has changed — but not why, under which policy or strategy, or with what resources.

    This opacity limits both public accountability and corporate ESG transparency, weakening the coherence required by SDG 17.14 – Policy Coherence for Sustainable Development.

    PMC bridges that gap by giving every dataset its own policy DNA — linking data to the laws, strategies, or initiatives that produced it.
    It transforms information into traceable evidence that can be verified, audited, and meaningfully interpreted across public, private, and hybrid systems.

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    The Informational DNA of Governance

     PMC forms the metadata layer that connects data systems with their decision frameworks — whether governmental, corporate, or institutional.
    It links datasets and indicators to their policy, program, or investment origin, establishing a bidirectional chain of meaning between data and decision.

    Each record registered under PMC carries:

    • Reference – which policy, regulation, or strategy it supports.
    • Owner – the responsible institution, department, or business unit.
    • Budget or Project Code – what resources sustain it.
    • Temporal Scope – when the initiative is active.
    • Source Lineage – where and how the data was collected and verified.

    Together, these attributes make every metric explain not just the number, but its governance or management context — aligning with SDG 17.14’s call for integrated, coherent decision-making.

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    From Text to Actionable Metadata

     PMC operates through a three-stage intelligence pipeline:
    1️⃣ Clause Extraction — isolates obligations, principles, and actions from legal, policy, or corporate text.
    2️⃣ Metadata Encoding — assigns standardized attributes (subject, scope, timeframe, responsible party).
    3️⃣ Semantic Linking — connects related clauses and commitments across frameworks, revealing redundancies, contradictions, or synergies.

    This process turns static documents into a living governance and compliance graph, ready for AI reasoning, performance tracking, and coherence measurement across public administration, corporate governance, and ESG systems.

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    A Core Kernel for System Interoperability

     

    PMC functions as a metadata kernel within any organization or platform that requires structured, machine-readable policy or compliance data.
    It provides the data foundation for systems performing coherence analysis, regulatory monitoring, sustainability reporting, or impact assessment.

    By enabling clause-level traceability and semantic interoperability, PMC ensures that every commitment — from an SDG target to a corporate ESG goal — can be linked, compared, and audited.
    Its adaptable schema integrates into digital governance infrastructures, corporate dashboards, and AI-driven decision-support systems, creating a consistent informational layer across domains.

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    Call for partnerships

     PMC welcomes partnerships with institutions and enterprises advancing interoperable, evidence-based governance.
    Priority collaborations include:

    • National Statistical Authorities (NSAs) strengthening SDG 17.14 implementation through indicator lineage and policy integration.
    • Corporates and ESG leaders aligning sustainability data with strategy, risk, and compliance frameworks.
    • Standards bodies (SDMX, CSRD, ISO, IFRS) developing interoperable metadata schemas.
    • Public agencies and financial regulators enabling clause-level traceability between rules, budgets, and outcomes.
    • International organizations advancing the SDG 17.14 and OECD PCSD coherence agendas.

    PMC provides the metadata kernel linking policy, compliance, and strategy data, ensuring transparent, auditable, and interoperable intelligence across sectors.

PMC turns policy text into a shared, machine-readable language.

 Its layered design converts unstructured laws and strategies into traceable metadata and a governance graph. This enables semantic interoperability across public, private, and institutional systems, making policy coherence (SDG 17.14) auditable and explainable. 

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Turning unstructured governance data into interoperable intelligence


Each feature represents a building block of digital policymaking and metadata coherence. 

  • Clause Extraction Engine

     Transforms legal and policy text into structured metadata.
    Automatically identifies clauses, actors, timelines, and obligations from regulatory text.
    Output: Standardized clause objects for comparison and reuse. 

  • Metadata Schema Designer

     Defines how policies, standards, and plans interconnect.
    Establishes a unified taxonomy for obligations, indicators, and cross-references.
    Output: Machine-readable governance schema. 

  • Interoperability Graph Builder

    Connects policy metadata across jurisdictions and institutions.
    Enables multi-level coherence analysis by mapping dependencies and contradictions.
    Output: Interactive coherence graph and dependency map. 

  • Governance API Layer

     Feeds structured policy data into analytical and reporting systems.
    Provides real-time access for dashboards, compliance checks, and AI reasoning modules.
    Output: Live data streams for automated coherence reporting. 

Use Case: Tracing ESG Data Lineage in Corporate Reporting

 From fragmented sustainability data to verifiable governance intelligence — how PMC eliminates greenwashing risks and embeds audit-ready evidence within corporate ESG datasets. 

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