The binding constraint on bathymetric data sharing was never the absence of standards. It is the absence of machine-resolvable linkage between them. That is the measured conclusion of this review, and it reframes the problem from one of collection to one of architecture. We have spent decades perfecting how to measure the seafloor and comparatively little time ensuring those measurements can speak to each other across platforms, datums, and decades. The result is a global ocean observing system that is data-rich but integration-poor.
The review's mapping of hydrographic standards onto the FAIR principles is instructive precisely because it shows where the real gaps sit. Reusability is already demanding, with paired depth and uncertainty encoding and quantified survey-order thresholds baked into the standards. Interoperability, however, is met at the level of encoding, not semantics. The authoritative vocabulary of the domain is not published as dereferenceable identifiers. And findability is barely addressed at all: the identifiers specified by IHO S-100 are unique within an exchange set but not globally resolvable. In practical terms, this means a researcher can locate a dataset, but not the precise vertical datum transformation needed to use it correctly. This is not an abstract concern. It directly undermines the kind of integrated analysis required for climate indicators and coastal hazard assessment, which depend on stitching together observations from satellites, autonomous vehicles, and legacy surveys. The recent record-breaking climate years we have documented in 2024 Follows 2023, a Second Record Year of Rising Climate Indicators only sharpen the stakes: we cannot track accelerating change if the underlying data remain siloed by convention.
The review's conclusion that vertical-datum heterogeneity remains the least tractable barrier to specification alone is the point that deserves attention. No new sensor or survey campaign will solve this. It is a problem of shared reference frames, and it will only be resolved through deliberate, coordinated action on persistent identifiers and resolvable vocabularies. This is the same kind of systemic friction we see in other domains, such as the measurable regional divergence in shipping routes driven by geopolitical shocks, where fragmented data standards obscure the very signals that matter for operational decisions. The lesson is consistent: interoperability is not a technical luxury; it is a precondition for actionable ocean intelligence.
What this means for our readers, whether you are a hydrographer, a modeler, or a policy advisor, is that the next wave of progress will not come from another satellite or a faster autonomous vehicle. It will come from committing to publish authoritative vocabularies as dereferenceable identifiers and to make every vertical datum machine-resolvable. The standards exist; the linkage does not. That is a concrete, addressable gap. The question is whether the community will treat it with the same urgency as a new survey technology, or whether we will continue to let fragmented data infrastructure quietly cap the ceiling on our collective understanding. Watch for the first major hydrographic office to publish its datum transformations as resolvable identifiers. That will be the signal that the system is finally learning to integrate itself.