Kai-Uwe Sattler

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Typical approaches for querying structured Web Data collect (crawl) and pre-process (index) large amounts of data in a central data repository before allowing for query answering. However, this time-consuming pre-processing phase however leverages the benefits of Linked Data -- where structured data is accessible live and up-to-date at distributed Web(More)
While standardized and widely used benchmarks address either operational or real-time Business Intelligence (BI) workloads, the lack of a hybrid benchmark led us to the definition of a new, complex, mixed workload benchmark, called mixed workload CH-benCHmark. This benchmark bridges the gap between the established single-workload suites of TPC-C for OLTP(More)
Main memory processing and data compression are valuable techniques to address the new challenges of data warehousing regarding scalability, large data volumes, near realtime response times, and the tight connection to OLTP. The IBM Smart Analytics Optimizer (ISAOPT) is a data warehouse appliance that implements a main memory database system for OLAP(More)
A main problem of data integration is the treatment of conflicts caused by different modeling of real-world entities, different data models or simply by different representations of one and the same object. During the integration phase these conflicts have to be identified and resolved as part of the mapping between local and global schemata. Therefore,(More)
In recent years the support for index tuning as pan of physical database design has gained focus in research and product development, which resulted in index and design advisors. Nevertheless, these tools provide a one-off solution for a continuous task and are not deeply integrated with the DBMS functionality by only applying the query optimizer for index(More)
The idea of collecting and combining large public data sets and services became more and more popular. The special characteristics of such systems and the requirements of the participants demand for strictly decentralized solutions. However, this comes along with several ambitious challenges a corresponding system has to overcome. In this demonstration(More)
Peer Data Management Systems (PDMS) are a natural extension of heterogeneous database systems. One of the main tasks in such systems is efficient query processing. Insisting on complete answers, however, leads to asking almost every peer in the network. Relaxing these completeness requirements by applying approximate query answering techniques can(More)
Wireless sensor networks are powerful, distributed, self-organizing systems used for event and environmental monitoring. In-network query processors like TinyDB offer a user friendly SQL-like application development. Due to the sensor nodes’ resource limitations, monolithic approaches often support only a restricted number of operators. For this reason,(More)
Over the past few years, techniques for managing, querying, and integrating data on the Web have significantly matured. Well-founded and practical approaches to assess or even guarantee a required degree of quality of the data in these frameworks, however, are still missing. This can be contributed to the lack of welldefined data quality metrics and(More)
The need for large-scale data sharing between autonomous and possibly heterogeneous decentralized systems on the Web gave rise to the concept of P2P database systems. Decentralized databases are, however, not new. Whereas a definition for a P2P database system can be readily provided, a comparison with the more established decentralized models, commonly(More)