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A semantic comparison of the modelling capabilities of the ER and NIAM models

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Entity-Relationship Approach — ER '93 (ER 1993)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 823))

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Abstract

Conceptual design (conceptual modelling) is the most important phase in database design as it results in a conceptual schema, which is a high-level description of the user requirements. Over the past decade, several data models, called semantic or conceptual models, have been proposed for conceptual design. Two of the most popular of these data models are the ER and NIAM models. In this paper we present a semantic comparison of the ER and NIAM models with a view to highlighting their similarities and differences, and to showing the major characteristics of each model. The comparison is divided in three parts. Firstly, we describe and compare the model constructs using a common terminology framework. We then compare their modelling capability by discussing the mapping of ER and NIAM schemas into the relational model. Finally, we relate the models to a checklist of conceptual modelling objectives.

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Author information

Authors and Affiliations

  1. Departamento de Ciência da Computação, Universidade Federal de Minas Gerais, Caixa Postal 702, 30161-970, Belo Horizonte MG, Brasil

    Alberto H. F. Laender

  2. Department of Computation, UMIST, PO Box 88, M60 1QD, Manchester, UK

    Donal J. Flynn

Authors
  1. Alberto H. F. Laender
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  2. Donal J. Flynn
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Editor information

Ramez A. Elmasri Vram Kouramajian Bernhard Thalheim

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© 1994 Springer-Verlag Berlin Heidelberg

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Laender, A.H.F., Flynn, D.J. (1994). A semantic comparison of the modelling capabilities of the ER and NIAM models. In: Elmasri, R.A., Kouramajian, V., Thalheim, B. (eds) Entity-Relationship Approach — ER '93. ER 1993. Lecture Notes in Computer Science, vol 823. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0024371

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  • DOI: https://doi.org/10.1007/BFb0024371

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-58217-5

  • Online ISBN: 978-3-540-48575-9

  • eBook Packages: Springer Book Archive

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