NaLER: a natural language method for interpreting E-R models

Entity-relationship models continue to be the most common means of documenting the data requirements of information systems. Whether used as the basis for relational database design or to record organisational conceptual data structures if is essential that the information content (the semantics) of entity-relational models is clearly understood both by the builders and the users of such models. Research suggests that this understanding may not always be readily acquired. The paper details a practical method that has been developed for use by data modelling students. This method, termed NaLER (Natural Language for E-R), provides student modellers with a more organised way of both assessing the information content of the models that they and others had produced and also of comparing those models with the information contained within the original scenario. It is suggested that the method could be of practical benefit not only to students but to anyone wanting to ascertain the semantic content of a data model.