Accuracy in Modeling with Extended Entity Relationship and Object Oriented Data Models

Abstract

This research compares success in developing conceptual data models for the extended entity relationship (EER) model and Kroenke's object oriented model. A laboratory study was used to evaluate model correctness for 38 subjects divided into two equally sized groups where each group was trained in one of the modeling methods. Modeling correctness is measured in terms of eight different facets of a conceptual data model: (1) entities/objects, (2) attribute/property identifiers, (3) categories, (4) unary one-one relationships, (5) binary one-many relationships, (6) binary many-many relationships, (7) ternary one-many-many relationships, and (8) ternary many-many-many relationships. The EER model provided significantly improved performance for the attribute/ property identifier, unary one-one relationship, and binary many-many relationship facets. A number of research areas are concerned with human factors and database technology. These include information elicitation, query formulation, and data modeling. This paper focuses on data modeling and extends prior data modeling research by investigating the degree of model correctness achievable by entry-level information system professions for two methods commonly used to develop conceptual data models. Conceptual data models primarily use graphical symbols to represent data and data relationships in an implementation independent manner. Model correctness is important for the creation of properly working information systems. A conceptual data model can be incorrect in several ways, for

Consulting support during conceptual database design in the presence of redundancy in requirements specifications: an empirical study

“…There is no evidence that novice designers de"ne these dependencies before attempting normalization. There is evidence (Batra et al, 1990;Juhn & Naumann, 1985;Jarvenpaa & Machesky, 1989;Bock & Ryan, 1993), however, that novice designers commit signi"cantly more errors using the relational rather than using the ER model thus suggesting that an abstraction-based approach (like ER) is more likely to lead to promising results.…”

“…Among the conceptual modelling techniques, the ER representation has been shown to lead to superior performance in many experiments (e.g. Juhn & Naumann, 1985;Jarvenpaa & Machesky, 1989;Batra, Ho!er & Bostrom, 1990;Bock & Ryan, 1993). A representation in the ER format is easily and automatically translated into a popular format that facilitates implementation (e.g.…”

“…(1) Perceived complexity of the task: empirical studies have shown that novice designers commit a number of errors in the conceptual and the logical modeling phase (Juhn & Naumann, 1985;Jarvenpaa & Machesky, 1989;Bock & Ryan, 1993). As discussed earlier, the combinatorial complexity arises because given a limited number of entities, a large number of relationships are possible (Dullea & Song, 1997).…”

“…The ternary relationship has been studied or discussed in a number of articles and books (e.g. Hammer & McLeod, 1981;Teorey et al, 1986;Scheer, 1989;Teorey, 1990;Bock & Ryan, 1993;Shoval & Shiran, 1997;McFadden et al, 1998).…”

Evaluating the Quality of Process Models: Empirical Testing of a Quality Framework

“…3,4,5,7,8,10,17,22,25,26,28,30,31,32,33,34,36,40,46,47,48,49,53,57]. However, the issue of process model quality has received far less attention in the literature.…”