number. The statistical meaning is implicit, come from the references of the RFC: the only normative reference with something about uncertainty is the RFC 5491 (section 5). The main informative reference, ISO 6709:2008, not use the term "uncertainty", but use the terms "accuracy" and "precision", which are uncertainty facets and can be interpreted in accordance with ISO 5725-1 (illustrated). Putting all together, adopting these clues, the usual statistical assumptions, and the explicit definitions of the RFC, we obtain the Geo URI's uncertainty mathematical properties: uncertainty is symmetric: the RFC is explicit, and we can understand it as valid simplification hypothesis. "The single uncertainty value is applied to all dimensions given in the URI" (section 3.4.3). Results in a spherical volume around the point (or a disk by 2D projection).By RFC 5491 "locations are expressed as a point (...) and an area or volume of uncertainty around the point". Using RFC 5491, we can suppose that "It is RECOMMENDED that uncertainty is expressed at a confidence of 95% or higher". Therefore, the uncertainty is two standard deviations, 2σ, and it is the radius of the disk that represents uncertainty geometrically. fixed measure unit: the RFC obligate the use of meters as uncertainty measure units, even when coordinates (CRS) use other (like default that is decimal degrees). It is a semantic and a conversion problem: the Gaussian error model: RFC say nothing, we interpreting the phrases "amount of uncertainty in the location" and "the uncertainty with which the identified location of the subject is known", all in the context of the normative reference, RFC 5491 (and the informative references like ISO 6709:2008). adopting standard error model: the model of the most common descriptive statistics modeling. It is imposed, is independent of selection process of uncertainty description, there are no other choices. total uncertainty: it is only one parameter representing "all uncertainty", the uncertainty in the spatial measure and uncertainty about object definition or object's center. It is a sum of random variables. There is no simplification hypothesis defined to reduce it to a one-variable model. Imagining the location of an ant colony to illustrate: the colony is a 3D object at the (exactly) the Terrain surface, so at precise altitude (approximated to a zero uncertainty measure). the 3D object has some consensual definition, but it is not precise, so, its uncertainty can not be neglected. This lack of precision can be about