Abstract
Time is one of the dimensions we frequently find in data warehouses allowing comparisons of data in different periods. In current multi-dimensional data warehouse technology changes of dimension data cannot be represented adequately since all dimensions are (implicitly) considered as orthogonal. We propose an extension of the multi-dimensional data model employed in data warehouses allowing to cope correctly with changes in dimension data: a temporal multi-dimensional data model allows the registration of temporal versions of dimension data. Mappings are provided to transfer data between different temporal versions of the instances of dimensions and enable the system to correctly answer queries spanning multiple periods and thus different versions of dimension data.
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References
M. Blaschka. FIESTA: A Framework for Schema Evolution in Multidimensional Information Systems. In Proc. of 6th Doctoral Consortium, Germany, 1999.
M. Blaschka, C. Sapia, and G. Höfling. On Schema Evolution in Multidimensional Databases. In Proc. of the DaWak99 Conference, Florence, Italy, 1999.
M. Böhlen. Temporal Database System Implementations. SIGMOD, 24(4), 1995.
P. Chamoni and S. Stock. Temporal Structures in Data Warehousing. In Data Warehousing and Knowledge Discovery (DaWaK) 1999, p. 353–358, Italy, 1999.
S.M. Clamen. Schema Evolution and Integration. In Distributed and Parallel Databases: An International Journal, p. 2(1):101–126.
O. Etzion, S. Jajodia, and S. Sripada, editors. Temporal Databases: Research and Practise. LNCS 1399. Springer-Verlag, 1998.
Goralwalla, Tansel, and Zsu. Experimenting with Temporal Relational Databases. ACM, CIKM95, 1995.
Gregersen and Jensen. Temporal Entity-Relationship Models-a Survey. Time-Center, 1997.
C.S. Jensen and C.E. Dyreson, editors. A consensus Glossary of Temporal Database Concepts-Feb. 1998 Version. Springer-Verlag, 1998. In [6].
C. Li and X. Wang. A Data Model for Supporting On-Line Analytical Processing. ACM, CIKM 96, 1996.
C. Liu, S. Chang, and P. Chrysanthis. Database Schema Evolution using EVER Diagrams. In Proc. of the Workshop on Advanced Visual Interfaces, 1994.
A. Mendelzon and A. Vaisman. Temporal Queries in OLAP. In Proc. of the 26th VLDB Conference, Egypt, 2000.
SAP America, Inc. and SAPAG. Data Modelling with BW-ASAP for BW Accelerator. 1998. White Paper: URL: http://www.sap.com.
P. Vassiliadis and T. Sellis. A Survey of Logical Models for OLAP Databases. In SIGMOD Record 28, 1999.
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Eder, J., Koncilia, C. (2001). Changes of Dimension Data in Temporal Data Warehouses. In: Kambayashi, Y., Winiwarter, W., Arikawa, M. (eds) Data Warehousing and Knowledge Discovery. DaWaK 2001. Lecture Notes in Computer Science, vol 2114. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44801-2_28
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DOI: https://doi.org/10.1007/3-540-44801-2_28
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