Free Emissions Data Quality Assessment Framework

How the framework works

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Before committing to disclosures, you're guided through a step‑by‑step evaluation, designed both to reset your baseline and to pinpoint weaknesses before they become problems:

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Six core data quality dimensions

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The assessment is organised around six key elements — accuracy, completeness, timeliness, consistency, traceability, and reliability — each mapped to specific AASB S2 disclosure expectations to support external assurance readiness.

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Included assessment tools
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• Data quality checklist – Evaluate each emissions dataset with clear checkpoints: Do numbers align with financial or operational systems? Is the data current? Are methodologies applied consistently? You mark items as compliant or flag areas needing attention, giving you a transparent gap analysis.
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• Emissions data source register – Create a log of every data source (e.g., electricity, gas, refrigerants), noting department owners, system origins, formats, last updates, and verification status. This promotes accountability and traceability.
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• Methodology & assumptions log – Document every calculation in one place: the activity data, emission factors, assumptions, and data sources used. This becomes crucial evidence for audit and assurance reviewers.
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Together, these tools help you build a transparent, auditable, and compliant emissions dataset — so you're ready for both internal scrutiny and external verification.

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