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.