Abstract
Multidimensional data modeling plays a key role in the design of a data warehouse. We argue that the Entity Relationship Model is not suited for multidimensional conceptual modeling because the semantics of the main characteristics of the paradigm cannot be adequately represented. Consequently, we present a specialization of the E/R model — called Multidimensional Entity Relationship (ME/R) Model. In order to express the multidimensional structure of the data we define two specialized relationship sets and a specialized entity set. The resulting ME/R model allows the adequate conceptual representation of the multidimensional data view inherent to OLAP, namely the separation of qualifying and quantifying data and the complex structure of dimensions. We demonstrate the usability of the ME/R model by an example taken from an actual project dealing with the analysis of vehicle repairs.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
A, Bauer, W. Lehner: The Cube-Query-Language (CQL) for Multidimensional Statistical and Scientific Database Systems, Proc. of the 5th CIKM, Melbourne 1997.
M. Blaschka, C. Sapia, G. Höfling, B. Dinter: Finding Your Way through Multidimensional Data Models, DWDOT Workshop (DEXA 98), Vienna
S. Chaudhuri, U. Dayal: An Overview of Data Warehousing and OLAP Technology. SIG-MOD Records 26(1), 1997
P.P-S. Chen: The Entity Relationship Model — Towards a Unified View of Data. ACM TODS Vol. 1, No. 1, 1976
E. F. Codd: Extending the Database Relational Model to Capture More meaning. ACM TODS Vol. 4, No. 4 (December 1979)
L. Cabibbo, R. Torlone: A Logical Approach to Multidimensional Databases. EDBT 1998.
S. Dekeyser, B. Kuijpers, J. Paredaens, J. Wijsen: The nested datacube model for OLAP in Advances in Database Technology, LNCS, Springer Verlag
M. Golfarelli, D. Maio, S. Rizzi, Conceptual design of data warehouses from FIR schemes, Proc. 31st Hawaii Intl. Conf. on System Sciences, 1998.
V. Harinarayan, A. Rajaraman, J. D. Ullman: Implementing Data Cubes Efficiently. Proc. SIGMOD Conference, Montreal, Canada, 1996
G. Höfling, M. Blaschka, B. Dinter, P. Spiegel, T. Ringel: Data Warehouse Technology for the Management of Diagnosis Data (in German), in Dittrich, Geppert (eds.): Datenbanksysteme in Büro, Technik und Wissenschaft (BTW), Springer, 1997.
W. H. Inmon: Building the Data Warehouse, 2nd edition, John Wiley andSons, 1996
IRDS Framework ISO/IEC IS 10027, 1990
R. Kimball: A Dimensional Modeling Manifesto, DBMS Magazine, August 1997
W. Lehner, T. Ruf, M. Teschke: CROSS-DB: A Feature-Extended Multidimensional Data Model for Statistical and Scientific Databases, Proc. of the CIKM’96, Maryland.
Micro Strategy Inc.: The Case For Relational OLAP, White Paper. 1995
M. Rafanelli, A. Shoshani: STORM: A Statistical Object Representation, SSDBM 90
S.Y.W. Su: SAM*: A Semantic Association Model for Corporate and Scientific-Statistical Databases, in: Journal of Information Sciences 29, 1983
T.J. Teorey: Database Modeling and Design, 2nd edition, Morgan Kaufmann 1994
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1999 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Sapia, C., Blaschka, M., Höfling, G., Dinter, B. (1999). Extending the E/R Model for the Multidimensional Paradigm. In: Kambayashi, Y., Lee, D.L., Lim, EP., Mohania, M.K., Masunaga, Y. (eds) Advances in Database Technologies. ER 1998. Lecture Notes in Computer Science, vol 1552. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-49121-7_9
Download citation
DOI: https://doi.org/10.1007/978-3-540-49121-7_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-65690-6
Online ISBN: 978-3-540-49121-7
eBook Packages: Springer Book Archive