When Steve Crocker published RFC 1 on April 7, 1969, he did not present it as doctrine. He described tentative agreements, open questions, and a document offered in expectation of reaction (Crocker, 1969). That posture matters. It is a reminder that stewardship and governance were not late additions to shared technical infrastructure. They were part of its identity near the beginning.
That makes the anniversary of RFC 1 more than a historical curiosity. It offers a useful way to think about geospatial as well. Some of the field’s most important progress has depended not just on tools or code, but on the quieter work of carrying structure, coherence, and shared understanding forward over time.
RFC 1 matters here because it reflects how durable technical systems evolve. They depend on more than invention. They depend on open documentation, standards processes, and institutions capable of carrying technical coherence forward as the environment changes. The early internet evolved through that kind of structure. Open access to RFCs helped distribute protocol knowledge, and the community repeatedly adapted its coordination mechanisms as the network grew (Internet Society, n.d.).
Geospatial has its own version of that story. The comparison is not exact, and it does not need to be. The narrower point is enough. Shared infrastructure becomes more resilient when governance and stewardship are embedded in the technical culture rather than treated as afterthoughts. That posture makes later adaptation more achievable.
Geospatial has its own standards story, though it is not the story of a single institution acting alone. Important geospatial standards have emerged through different processes and communities. GeoJSON, for example, eventually moved through the IETF RFC process, not OGC. Even there, though, the inheritance is revealing. RFC 7946 notes that GeoJSON’s concepts were derived from pre-existing open geographic information system standards and states explicitly that its seven concrete geometry types come from the OpenGIS Simple Features specification (Butler et al., 2016).
That is part of the larger point. The value of standards work is not simply that documents exist. It is that years of collaborative work created a common structural baseline for geospatial data and services. OGC’s first standard was Simple Features in 1997, followed in the years after by standards such as Web Map Service and Geography Markup Language (OGC, n.d.). Simple Features in particular has had unusual staying power. Its geometry model remains deeply embedded in databases, formats, and software well beyond the confines of any one standards body (OGC Simple Features, n.d.).
That kind of consistency is easy to miss because it becomes ordinary. But ordinary is exactly the point. When geometry types, feature structures, and core spatial concepts remain recognizable across tools and systems, translation distance declines. Interoperability is never complete, and standards work is never final, but the field is still far more structured than it would be otherwise. That structure did not appear on its own. It was maintained, refined, and carried forward.
This is where stewardship becomes visible in positive form. It is not just what prevents fragmentation. It is also what allows value to compound. Geospatial innovation today benefits from structures that have been maintained, refined, and reused over long periods of time. That does not make standards bodies infallible, and it does not mean every standards effort succeeds equally well. It does mean that modern geospatial work, including geospatial AI, is building on inherited order rather than starting from zero.
AI doesn’t make this history less relevant. It makes it harder to ignore. One reason is that AI systems are unusually good at consuming whatever structure already exists. Consider the way contemporary Earth observation workflows increasingly rely on STAC metadata. The OGC STAC Community Standard defines machine-readable structure for catalogs, collections, and items, with required fields such as links, extents, and licenses, and it treats a STAC Item as a GeoJSON feature with additional spatiotemporal metadata (OGC STAC Community Standard, n.d.). That kind of inherited structure does not eliminate ambiguity, but it does reduce it. It gives downstream systems, including AI-assisted ones, more consistency to work with.
The second reason is less flattering. AI is also very good at exposing where order is thin, where provenance is unclear, and where authority is assumed rather than demonstrated. A model can still produce a plausible answer under those conditions. That is precisely the problem. Plausibility is not a substitute for traceability, context, or confidence. NIST’s generative AI profile makes this concrete by calling for documentation of training data sources to trace the origin and provenance of AI-generated content and by emphasizing governance, transparency, and documentation as part of trustworthy deployment (NIST, 2024).
That is why the next stewardship problem is not simply to preserve what earlier standards work made possible. It is to decide how geospatial knowledge should be governed as it is mediated by models and agents. Questions of provenance, interpretability, authority, and accountability do not sit outside the technical system. They are its foundation.
The anniversary of RFC 1 is a useful reminder that governance and stewardship are not foreign to technical work. They have long been part of how durable shared infrastructure is built. Geospatial has its own version of that history. Standards work, including the long life of Simple Features and the continued evolution of newer specifications, helped create a field that is more structured, more portable, and more interoperable than it otherwise would have been (Crocker, 1969; OGC history, n.d.; OGC Simple Features, n.d.).
That is worth remembering now because AI will not govern itself. If geospatial AI is going to be trustworthy, its foundations will need more than model performance. They will need provenance that can be traced, authority that can be explained, and accountability that institutions are prepared to own. In that respect, the next stewardship problem is not separate from the earlier ones. It is a continuation of them.
The technical foundations that matter most are rarely only technical. That was true near the beginning of the internet era. It has been true in geospatial standards work. It is likely to be even more true in the years ahead.
Header image: Idéalités, CC BY-SA 4.0 https://creativecommons.org/licenses/by-sa/4.0, via Wikimedia Commons
