Werner Dreyer

Learn More
Empirical research based on time series is a data intensive activity that needs a data base management system (DBMS). We investigate the special properties a time series management system (TSMS) should have. We then show that currently available solutions and related research directions are not well suited to handle the existing problems. Therefore, we(More)
The analysis of time series is a central issue in economic research and many other scientific applications. However , the data management functionality for this field is not provided by general-purpose DBMSs. Therefore, we propose a data model of a specialized Time Series Management System (TSMS) which accounts for these needs. The model is centered around(More)
In financial institutions, time series are important for economic and financial research as well as for various non-research related activities like portfolio management. In general, scientific applications make extensive use of time series. Using traditional general-purpose DBMS proves inadequate for the requirements of this domain. We show how to cope(More)
The distribution of data within or between organizations is crucial for many applications. Such a distribution may be transparent, as it is embodied in distributed database systems to increase their performance, reliability and availability. Other systems either do not require transparent data distribution or even explicitly need their own copies of the(More)
This paper analyzes how financial researchers manage large numbers of time series and how they work with these data. We show that replication services are a central facility of a time series management system and we define the requirements for such replication services. An evaluation of current time series management systems shows that they do not support(More)
  • 1