Mobile augmented reality
 Ubiquitous, multi-ontology
In the Workshop on Semantic Web Technology for Mobile and Ubiquitous Applications, ISWC 2004, A. Qasem, J. Heflin and H. Muñoz-Avila wrote, in their paper Efficient Source Discovery and Service Composition for Ubiquitous Computing Environments, that "to be truly pervasive the devices in a ubiquitous computing environment have to be able to form a "coalition" without human intervention." This requires multi-ontology sense-making and ontology perspectives that simulate human perspective (see where are your feet for more on this issue.)
 Requires an active risk-reducing ontology
Living ontology is supposed to be both an active ontology (with a risk-reducing capability) and a mapping ontology, independent of any given infrastructure and of any phase of its development, i.e. just as useful in planning and building it, as repairing it, and in augmenting it during a crisis when it's overburdened or partly incapacitated. Because MAR can challenge these assumptions, and is useful at all points in the process including during a crisis, LO avoids:
- tense assumptions (past, present, future) - property or perspective assumptions (we, they, our) - infrastructure assumptions ("computer", "building") - commitment assumptions (esp. command and control) - any bias that chaotic or complex situations can be treated as if merely complicated (see chaotic/complex/complicated) - time biases (become/remain/equal rather than "is")
 Requires source relevance model
Qasem, Heflin and Muñoz-Avila propose that the semantic web can provide "the infrastructure for discovery and composition of device functionalities. AI planning has been a popular technology for automatic service discovery and composition in the Semantic Web. However, because the Web is so vast and changes so rapidly, a planning agent cannot make a closed-world assumption. This condition makes it difficult for an agent to know when it has gathered all relevant information or when additional searches may be redundant." In other words, there is no simple way to tell when the services available are adequate to the purpose, since the purpose cannot be described well enough. Some aspects, however, such as the price of services, may be directly useful to determine whether to continue any such search.
However, mobility and geolocation and the danger of distracting end users while they move in the real world, limit the relevance of sources. One in the proximity of the user, for instance, may have much more relevance. One with more volatility may indicate more relevance since its versions are changing faster.
Using local closed world reasoning with HTN planning to compose Semantic Web services, Q, H and M-A implemented a model of source relevance that provides minimal evidence/source/authority for the argument that a source is useful for the user's purpose. The authority consists of inference using the semantic web itself, the evidence is the claim that the service is useful to the purpose (though it may actually be spam or otherwise misrepresented).