Big Data Analytics

We are a group of computer scientists with ten years of experience developing data exploration and analysis methods in interdisciplinary research projects for

Our research is motivated by real-world scientific applications such as remote sensing (e.g., change detection), fluid systems modeling (e.g., construction of surrogate models), earth system modeling (e.g., explaining the decisions of neural networks), investigation of floods (e.g. exploration of events).

We adopt computer science methods from 

  • machine-learning/artificial intelligence, 
  • interactive visualization, 
  • scientific workflows, and 
  • component-based software development 

to the specific requirements of real-world scientific applications. Our research is grounded in computer science. We develop our methods by engaging in a "dialogue" with scientists to determine the requirements of their scientific applications.

Our research supports scientists to conduct the essential steps of data-intensive science: to identify appropriate data, to understand data's properties,  to extract relevant structures and patterns from the data, to interpret the extracted information. We understand data-intensive science as the scientific approach integrating data from different sources and sensors and extracting relevant information from integrated data that were otherwise not apparent for scientists.

Research Areas

Find Relations among heterogeneous data

Geoscientists make use of data from sensors, geoarchives (such as core samples), and simulations to study the system Earth. The data describe Earth processes on various scales in space and time and by many different variables. Our methods facilitate the comparison of data from different sources and the integrated analysis of the heterogeneous data.

Research & Technologies:

Extract relevant information from large data sets

Current simulation models as well as observation systems generate large quantities of data. Our methods extract the important information from these data and present it in a compact and efficient manner to scientists.

Research & Technologies:

Exploration of multi-dimensional data

Geoscientists need to understand the behavior of Earth system processes based on multi-dimensional data. Our solutions enable scientists to explore spatio-temporal data to detect relevant information from multi-dimensional data.

Research & Technologies:


Mike Sips
Group Leader
Dr. Mike Sips
Remote Sensing and Geoinformatics
Building A 20, Room 303
14473 Potsdam
+49 331 288-1982