Ternary Relationships

Author(s):  
Trevor H. Jones ◽  
Il-Yeol Song

Conceptual data modeling is a backbone of most major systems development projects. Within this arena, one of the most widely used techniques is the entity-relationship (ER) or extended entity-relationship model (EER, henceforth also referred to as ER), introduced by Chen (1976). However, there are multiple competing models and notations, each having distinct strengths and weaknesses. Many of the model definitions and underpinnings continue to undergo practical and theoretical development. The abilities of each of the model structures and notations to fully represent the semantics of any given situation are constantly compared, with many issues open to argument. More specifically, certain arguments revolve around the inclusion of binary or N-ary representation of relationships in ER models. A central argument stems from the superior ability of N-ary modeling to reflect the true semantics of any given situation, whereas a binary model provides the simplest constructs for expressing information systems’ logical design and is equivalently represented in a relational database management system (DBMS) (McKee & Rodgers, 1992).

2019 ◽  
Vol 30 (1) ◽  
pp. 1-21
Author(s):  
Ljubica Kazi ◽  
Zoltan Kazi

Conceptual data models can change during the information system development and teamwork phases, which require constantly monitoring with synonyms detection. This study elaborates on an approach for detecting synonyms in an entity-relationship model based on mapping with ontological elements. The use of a specific data model validator (DMV) tool enables formalization of the ontology and ER models, as well as their integration with the set of reasoning rules. The reasoning rules enable mapping between formalized elements of the ontology and ER model, and the extraction of synonyms. Formalized elements and reasoning rules are processed within Prolog for the extraction of synonyms. An empirical study conducted by using university student exams demonstrates usability of the proposed approach. The results show effectiveness in extraction of synonyms in all types of conceptual data model elements.


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