Modeling Temporal Consistency in Data Warehouses

Abstract:

Real-world changes are generally discovered delayed by computer systems. The typical update patterns for traditional data warehouses on an overnight or even weekly basis enlarge this propagation delay until the information is available to knowledge workers.
The main contribution of the paper is the identification of two different temporal characterizations of the information appearing in a data warehouse: one is the classical description of the time instant when a given fact occurred, the other represents the instant when the information has been entered into the system. We present an approach for modeling conceptual time consistency problems and introduce a data model that deals with timely delays and supports knowledge workers to determine what the situation was in the past, knowing only the information available at a given instant of time.

Authors:

Robert M. Bruckner
Institute of Software Technology, Vienna University of Technology, Austria.

Beate List
Institute of Software Technology, Vienna University of Technology, Austria.

Josef Schiefer
IBM Watson Research Center, New York, USA.

A M. Tjoa
Institute of Software Technology, Vienna University of Technology, Austria.
 

Publishing Information:

In 12th International Workshop on Database and Expert Systems Applications (DEXA'01), IEEE Computer Society Press, pp. 901-905, Munich, Germany, September 2001.