Spatial Data Infrastructure, Rebuilt for the Age of AI

Portolan is presented as an open, cloud-native approach to spatial data infrastructure designed to improve how authoritative geospatial data is published, discovered, queried, and governed. It responds to limitations of traditional portals and API-based services by enabling publishers to store data in open formats such as GeoParquet, Cloud-Optimized GeoTIFF, PMTiles, and potentially Apache Iceberg, allowing users and applications to query files directly from publisher-controlled object storage. The approach combines standardized STAC catalogs, human-readable documentation, agent-oriented guidance, validation tools, and a registry of independently hosted catalogs to support federation without centralizing datasets. The text argues that AI agents can make these distributed data sources more accessible by discovering relevant datasets, performing reproducible spatial analyses, and returning sourced results, while open formats and separable choices of storage, compute, AI models, and semantics support data sovereignty. CARTO SDI is described as a commercial implementation built around the open Portolan catalog, adding catalog interfaces, natural-language AI access, governance, permissions, telemetry, quality controls, monetization, and support for legacy GIS services while leaving data in the publisher’s chosen storage environment. The initiative remains early, with approximately 20 registered catalogs, and seeks broader adoption, format support, client integrations, and independent implementations.

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