Abstract
There are many data modelling languages used in today’s information systems engineering environment. Some of the data modelling languages used have a degree of hype surrounding their quality and applicability. We would like to understand exactly what makes some data modelling languages successful and in some way suggest how useful data modelling languages will be in the context of an organisation and why. We are also interested in a theory capable of unifying the disparate range of languages. To do these things we select a theory based on ontology using which data modelling languages can be investigated. In this context theory should allow us to understand, compare, evaluate, and strengthen data modelling languages. The theory may also be used to suggest how useful various data modelling languages may be in an organisational setting. In this paper we present Chisholm’s ontology which we use to investigate data modelling languages. We show how Chisholm’s ontology can be used as a unifying theory of data models, develop methods for comparing data modelling languages based on this theory and summarise our findings. In conclusion, we evaluate the methods and the theory and examine avenues for future research. In this paper we present a deeper understanding of method together with analysis of new data modelling languages.
Recommended Citation
Milton, Simon; Kazmierczak, Ed; and Keen, Chris, "Data Modelling Languages: An Ontological Study" (2001). ECIS 2001 Proceedings. 100.
https://aisel.aisnet.org/ecis2001/100