This post details the challenges and architectural decisions made by CivicDataForge in transforming government open data into agent-callable evidence. It highlights issues such as data pagination limits, the ambiguity of "no match" results, and the critical need to preserve provenance through normalization. The authors propose a structured evidence envelope to maintain lineage and context, ensuring that data can be reliably used as evidence by AI agents. AI
IMPACT Provides a framework for reliably integrating diverse data sources for AI agents, improving data integrity and trustworthiness.
RANK_REASON The article describes a specific technical approach and challenges in building a data integration system, rather than a novel product release or research breakthrough.
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