Querying Time Interval Data

Philipp Meisen, Diane Keng, Tobias Meisen, Marco Recchioni, Sabina Jeschke

Abstract: Analyzing huge amounts of time interval data is a task arising more and more frequently in different domains like resource utilization and scheduling, real time disposition, as well as health care. Analyzing this type of data using established, reliable, and proven technologies is desirable and required. However, utilizing commonly used tools and multidimensional models is not sufficient, because of modeling, querying, and processing limitations. In this paper, we address the problem of querying large data sets of time interval data, by introducing a query language capable to retrieve aggregated and analytical results from such a database. The introduced query language enables analysis of time interval data in an on-line analytical manner. It is based on requirements stated by business analysts from different domains. In addition, we introduce our query processing, established using a bitmap-based implementation. Finally, we present and critically discuss a performance analysis.