Research

With a strong background in deductive databases, our research aims at extending existing database systems by new functionalities for directly supporting  in-database analytics, predictive reasoning and stream processing in monitoring applications. In particular we focus on necessary database language extensions for supporting this kind of analysis. To this end, we develop new operators for SQL, new optimization techniques for incremental stream processing as well as new graphical tools for defining and optimizing temporal database queries. For a list of our publications click here.

Projects (past)

• AIMS (Airspace Monitoring System) - A database tool for monitoring and analyzing flight data streams for detecting anomalies  in airspace in real-time.
• OpenResearch -  A crowdsourcig platform to provide information about scientific events, research groups, publications, tools, projects etc.
  

• CiteStats (Citation Statistics) - Enhanced analysis of the interrelationships of research papers and automatic detection of research schools based on bibliographical data.

• STATES (Phase Management in Database Systems) -  In this project we develop a tool for monitoring and analyzing situations detected within a stream of events.
  
• TinTo (Technical Investor Tool) - A database tool for continuously computing arbitrary technical indicators over streams of stock market data.
  
• CowMon (Dairy Cow Monitoring System) - A database tool for determining disease risk indicators for dairy cows using continuously observed animal data such as milk flow, water intake, activity and feed amounts.
  
• DatalogLab - An experimental deductive database system with enhanced features for recursive query evaluation.