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interpretation house_import :
base1 to House=
Agent
Person
ontology boat_house=
combine boat_personification, house_import
with Agent Boat , House BoatHouse
As before, Ontohub is able to compute the colimit. As above, we present here only
the relevant declarations of the blended concept.
Class : BoatHouse
SubClassOf :Artifact
and is_located_on some Plot
and has_function some ServeAsResidence
Class :ArtifactThatExecutesResidenceFunction
EquivalentTo :Artifact
and executes some ServeAsResidence
SubClassOf :is_inhabited_by some Boat
Figure 9.5 shows the representation of the ontologies and their relations in Ontohub.
Of course, the possibilities for blending the two concepts do not stop here. For
example, we could map the agent in the base ontology to person in the boat
ontology. This can be achieved by first defining an additional interpretation and by
blending all three interpretations.
interpretation boat_import :
base1 to Boat =
Agent
Person
ontology boat_house=
combine boat_personification, house_import ,
boat_import
with Agent Boat , House BoatHouse
The resulting blendoid is consistent, but it contains some strange consequences.
For example, in the blendoid boats are driven by boats. However, if we are interested
both in hosting boats and a hub for autonomous vehicles, this would count as an
interesting result. In general, whether such more creative aspects of blendoids are
desirable or not will depend on the context of the blending. We will address this issue
in the section on evaluation below. It should be noted, however, that an ontologically
cleaner axiomatisation of the input spaces makes blending in fact easier—this is
because it reveals more clearly the type structure of the inputs, whose modification
can then be more elegantly controlled via the base morphisms.
9.4.2 Variations: Blends of Blends and Partiality
We have discussed a more sophisticated version of the classic
blend-
ing in order to illustrate some of the fine detail in the workings of formalised blending
House + Boat
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