  In recent years, several efforts have been made to enhance conceptual data
modelling with automated reasoning to improve the model's quality and derive
implicit information. One approach to achieve this in implementations, is to
constrain the language. Advances in Description Logics can help choosing the
right language to have greatest expressiveness yet to remain within the
decidable fragment of first order logic to realise a workable implementation
with good performance using DL reasoners. The best fit DL language appears to
be the ExpTime-complete DLRifd. To illustrate trade-offs and highlight features
of the modelling languages, we present a precise transformation of the mappable
features of the very expressive (undecidable) ORM/ORM2 conceptual data
modelling languages to exactly DLRifd. Although not all ORM2 features can be
mapped, this is an interesting fragment because it has been shown that DLRifd
can also encode UML Class Diagrams and EER, and therefore can foster
interoperation between conceptual data models and research into ontological
aspects of the modelling languages.
