Semantic data models

• Main Authors: Joan Peckham, Fred Maryanski
• Other Authors: The Pennsylvania State University CiteSeerX Archives
• Format: Text
• Language: English
• Published: 1988
• Subjects: Categories and Subject Descriptors; D.2.1 [Software Engineering; Requirements/ Specifications-methodologies; D.2.10 [Software Engineering; Design; D.3.2 [Programming Languages; Language Classifications-design languages; H.2.1 [Database Management; Logical Design-data mode & H.2.3 [Database Management; Languages-data description languages (DDL; data manipulation languages (DML; query Zangqes; H.2.8 [Database Management; Database Applications; 1.2.4 [Artificial Intelligence; Knowledge Representation Formalisms and Methods-semantic networks; K.6.3 [Management of Computing and Information Systems; Software Management-software development General Terms; Languages Additional Key Words and Phrases; Conceptual data models; database systems; data models; DML
• Online Access: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.455.137; http://pdf.aminer.org/000/832/941/semantic_data_models.pdf

Semantic data models have emerged from a requirement for more expressive conceptual data models. Current generation data models lack direct support for relationships, data abstraction, inheritance, constraints, unstructured objects, and the dynamic properties of an application. Although the need for data models with richer semantics is widely recognized, no single approach has won general acceptance. This paper describes the generic properties of semantic data models and presents a representative selection of models that have been proposed since the mid-1970s. In addition to explaining the features of the individual models, guidelines are offered for the comparison of models. The paper concludes with a discussion of future directions in the area of conceptual data modeling.