Christian Koncilia

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A data warehouse (DW) provides an information for analytical processing, decision making, and data mining tools. On the one hand, the structure and content of a data warehouse reflects a real world, i.e. data stored in a DW come from real production systems. On the other hand, a DW and its tools may be used for predicting trends and simulating a virtual(More)
In data warehouses measures are analyzed along different dimensions. Although the structures of these dimensions change over time, data warehouse tools currently in use are not able to deal with these modifications in a sophisticated way. In this paper we present a bitemporal extension of the COMET metamodel. This extension enables us to represent not only(More)
Changes in transaction data are recorded in data warehouses and sophisticated tools allow to analyze these data along time and other dimensions. But changes in master data and in structures, surprisingly, cannot be represented in current data warehouse systems impeding their use in dynamic areas and/or leading to erroneous query results. We propose a(More)
Ontologies are shared conceptualizations of certain domains. Especially in legal and regulatory ontologies modifications like the passing of a new law, decisions by high courts, new insights by scholars, etc. have to be considered. Otherwise, we would not be able to identify which knowledge (which ontology) was valid at an arbitrary timepoint in the past.(More)
Data Warehouses provide sophisticated tools for analyzing complex data online, in particular by aggregating data along dimensions spanned by master data. Changes to these master data are a frequent threat to the correctness of OLAP results, in particular for multi-period data analysis, trend calculations, etc. As dimension data might change in underlying(More)