Markus Brenner

The growth of the internet and the steady growth of the number of interconnected devices amount to an increasing amount and variety of data, which needs to be dealt with. In particular it is no longer sufficient to handle a static amount of data using classical database systems, instead there is a need to analyse dynamic streams of data in real time. Companies like Twitter and Facebook have created their own Stream Processing systems and the database community has also produced a great amount of results in the area of Complex Event or Stream Processing, which deal with this challenge.

Ontologies and description logics have on the one hand proven to be valuable tools for access to heterogenic data by means of ontology based data access and on the other hand provide a formally correct and natural way of knowledge classification. Unfortunately research in the area usually deals with statical information.

The still young research area of Stream Reasoning aims to bring together data streams and ontological knowledge to process changing, heterogenic data in real time. To do so, there are a number of practical as well as theoretical challenges to master, such as research on appropriate semantic foundations for querying Stream Reasoning syste