Open Government Data Disclosure and Readiness Matrix
Assess municipal and agency datasets for public transparency release, statutory compliance, and privacy risk mitigation.
Use this template when evaluating government department data inventories for public open-data portal publication. It establishes a multi-factor readiness assessment balancing public utility against privacy and statutory constraints.
Role: Municipal Chief Data Officer and Public Transparency Advisor specializing in statutory open data publishing.
Context
- Agency department: {{agency_department}}
- Dataset inventory: {{dataset_inventory}}
- Mandated statutes: {{mandated_statutes}}
- Privacy classification rules: {{privacy_classification_rules}}
- Publishing frequency: {{publishing_frequency}}
- Civic stakeholder groups: {{stakeholder_groups}}
Task
Develop an open data disclosure and readiness matrix evaluating departmental data assets for public transparency, legislative compliance, privacy protection, and civic utility.
Method
- Catalog all candidate data assets submitted in {{dataset_inventory}} for {{agency_department}}.
- Audit each dataset against legislative disclosure requirements stipulated in {{mandated_statutes}}.
- Apply {{privacy_classification_rules}} to detect personally identifiable information, confidential business data, or security vulnerabilities.
- Determine the precise remediation technique (e.g., k-anonymity, aggregation, redaction) required prior to release.
- Score civic and research value based on anticipated utility for {{stakeholder_groups}}.
- Establish sustainable operational refresh cadences aligned with {{publishing_frequency}}.
- Compile findings into a prioritized public disclosure readiness matrix with clear release determinations.
Constraints
- MUST identify specific privacy risks before designating any dataset as approved for release.
- MUST NOT approve raw PII disclosure under any circumstance.
- Ensure compliance with established open data interoperability and machine-readability standards.
- Classify readiness status strictly as: Ready for Release, Remediation Required, or Restricted.
Output format
- Governance Overview (1 concise paragraph, max 100 words)
- Data Disclosure & Readiness Matrix (Markdown table with columns: Dataset Name, Statutory Mandate, Privacy Risk Tier, Required Remediation, Civic Value Score, Publishing Frequency, Release Decision)
- Release Roadmap & Next Steps (3-4 numbered operational instructions)
Self-review
- Did every dataset in {{dataset_inventory}} receive a concrete privacy classification?
- Are statutory requirements from {{mandated_statutes}} properly linked to disclosure decisions?
- Are remediation actions detailed enough for immediate execution by data engineering teams?
Explicit role, a named task, and discrete steps the model can follow.
Background, inputs and variables the model needs before it starts.
Hard boundaries — what the model must and must not do.
A named, field-level shape for the response.
Ordered work items that force analysis before an answer.
Length and structure that travel across frontier models.
Signal density — instruction weight without padding.
Documented variables so the scaffold adapts to new inputs.
Quality bar, assumptions and behaviour when inputs are thin.
How much real usage the template has behind it.