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coding. In a similar way, we derived three ARIS meta models that highlighted excess,
overload and redundancy in ARIS. Such models form a very intuitive way of representing
the identified ontological shortcomings. The underlying clustering of the models also
helps to quickly comprehend the main areas in which there are shortcomings.
At the present time, the process of an ontological analysis results in the identification
of ontological incompleteness and ontological clarity through the identification of
missing, overloaded or redundant grammatical constructs. While the end result identifies
such problems, it fails to account for their relative importance. For example, thing is one
of the fundamental constructs of the BWW model. Therefore, a lack of mapping to a
modelling grammar for this construct should be considered a more important shortcoming
than the lack of mapping for, say, the well-defined event construct. There is a need for
the development of a scoring model that enables the calculation of the 'goodness' of a
grammar with respect to the ontology. In such a scoring model, each of the ontological
constructs has a value assigned to it that reflects the relative importance of the construct
in the ontology. Core constructs would therefore have high weightings whereas less
important constructs would attract lower weightings. Following an ontological analysis
of a particular grammar, the weighting of all missing constructs would be calculated to
arrive at one value that generally reflects the outcome of the analysis.
An example for such a classification could have the following structure. All core con-
structs of an ontology (and the modelling grammar) would get the value one. All other
constructs represented as an entity type in the meta model of the ontology would receive
the value 0.7, and all other constructs get the value 0.3. Such a weighting would then
be applied to the outcomes of the ontological analysis. The scores would be aggregated
across the ontology and modelling grammar. They could also be calculated separately
for completeness, excess, overload and redundancy. Furthermore, they could be aggreg-
ated per cluster, which allows a more differentiated view of the particular strengths or
weaknesses of a modelling grammar. Though the consolidated score of such an evaluation
should not be overrated, it provides better insights into the characteristics of the onto-
logical deficiencies and provides a first rating of the significance and importance of the
identified shortcomings.
Apart from the lack of result classification that is addressed by the scoring model, another
problem with the outcome of the analyses has been the perceived lack of relevance of
the results. Since most modelling grammars focus on modelling a subset of the phenomena
that occur in the real world, it would follow that not all constructs of an ontology are
necessary in order to analyse such a grammar. If the full ontology is used in the analysis,
the result may identify potential problems that would not, in reality, occur, because the
modelling grammar is not used to model any phenomena described by the missing con-
structs. Further, there may also be a need for specialisation of some of the ontological
constructs in order to enhance analysis of a grammar pertaining to a particular domain.
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