In this group, we perform research in Computer Science in an interdisciplinary setting with a particular focus in sciences, such as Archeaology, as well as Geo-, Climate, and Marine Science. In such an interdisciplinary environment we research, develop and apply state-of-the-art information technologies in order to discover patterns, trends and relationships between objects in vast, potentially unstructured and heterogeneous data collections. To this end we develop methodologies in areas such as data literacy, data fusion, data mining, machine learning, knowledge discovery, and efficient search methods with a particular interest in spatial and spatio-temporal data. For example, with computer-aided methods we can model and explore complex processes, such as intelligent traffic and transport systems, geophysical and biological processes in Ocean Data Science, or socio-environmental transformations in Geo-Archaeo Data Science.

Studies on data structures, methods and algorithms for scalable data-driven exploration on heterogeneous data:

• Enriched Geo
• High Dimensional Data
• Multimedia
• Streams