An important use of data warehousing is to provide temporal views over the history of source data that may itself be non-temporal. While recent work in view maintenance is applicable to data warehousing, only non-temporal views have been considered. In this paper, we introduce a framework for maintaining temporal views over non-temporal information sources in a data warehousing environment. We describe an architecture for the temporal data warehouse that automatically maintains temporal views over non-temporal source relations, and allows users to ask temporal queries using these views. Because of the dimension of time, a materialized temporal view may need to be updated not only when source relations change, but also as time advances. We present incremental techniques to maintain temporal views for both cases.
CITATION STYLE
Yang, J., & Widom, J. (1998). Maintaining temporal views over non-temporal information sources for data warehousing. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1377 LNCS, pp. 389–403). Springer Verlag. https://doi.org/10.1007/bfb0100998
Mendeley helps you to discover research relevant for your work.