Adddress
Institute of Computer Science
Im Neuenheimer Feld 348
69120 Heidelberg
Phone: +49 (0) 6221 / 54-5711
Fax: +49 (0) 6221 / 54-5684
Email: gertz(at)informatik.uni-heidelberg(dot)de
Research
The database systems group is involved in various multi-disciplinary research acitivites not only with researchers in Computer Science but also researchers in environmental and atmospheric sciences, ecology, climatology, remote-sensing, geology, physics and cosmology, bioinformatics, and many other disciplines. The (former) projects below give a good overview of what type of fundamental and cutting-edge research our group is doing and how data management and database models, techniques, and architectures are applied in respective project areas.
Region Outliers in Sensor Networks
Sensor networks play an important role in applications concerned with environmental monitoring, disaster management, and policy making. Effective and flexible techniques are needed to explore unusual environmental phenomena in sensor readings that are continuously streamed to applications. In this work, we develop models and techniques that allow to detect outlier sensors and to efficiently construct outlier regions from respective outlier sensors. For this, we utilize the concept of degree-based outliers. Compared to the traditional binary outlier models (outlier versus non-outlier), this concept allows for a more fine-grained, context sensitive analysis of anomalous sensor readings and in particular the construction of heterogeneous outlier regions. The latter suitably reflect the heterogeneity among outlier sensors and sensor readings that determine the spatial extent of outlier regions. Such regions furthermore allow for useful data exploration tasks. We demonstrate the effectiveness and utility of our approach using real world and synthetic sensor data streams.
Temporal Information Retrieval
Temporal Information Retrieval
Time has been a subject of study in many disciplines particulary in philosophy, physics, and art. Time is an important dimension of any information space, and it can be very useful in information retrieval. A quick look at any of the current search engines shows that the temporal aspect is restricted to sort the hit list by the date attribute only. In this project, together with Omar Alonso and Ricardo Baeza-Yates, we study different ways in which temporal information explicit or implicit in documents and document collections can be used to cluster hit-lists based on time, profile documents based on their time properties, and explore search results using timelines.
GeoStreams
http://geostreams.ucdavis.edu
In this NSF funded research project we developed models, techniques, and architectures for the adaptive processing of real-time remotely-sensed, streaming geospatial image data, in particular from the National Oceanic and Atmospheric Administration’s (NOAA) Geostationary Operational Environmental Satellite (GOES).
COMET
COMET: COast-to-Mountain Environmental Transect
This NSF-funded project will develop a state-of-the-art cyberinfrastructure to facilitate climate research in a transect spanning from Bodega Bay to Lake Tahoe. The cyberinfrastructure will be based around the integration of access to distributed and varied data collections and sensor data streams, semantic registration of data, models and analysis tools, semantically-aware data query mechanisms, and an orchestration system for advanced scientific workflows. Access to this cyberinfrastructure will be provided through a Web-based portal. Prof. Dr. Michael led this project until he moved from UC Davis to the University of Heidelberg.