Metadata and Information Systems
About
The quality and availability of scientific data are essential for data-driven research and data science. While modern methods generate vast amounts of complex research data, documentation and management practices often fail to keep up. This gap has made information and data management a critical research area. Our multidisciplinary team is dedicated to advancing research data-aware information engineering, with the goal of harmonizing and integrating scientific data across domains, thereby enabling enhanced data analysis and reuse.
Research Topics
The MIS group designs and curates information infrastructures, such as large-scale knowledge graphs, that integrate diverse information assets to help scientists easily find relevant research data. Through collaboration with scientific communities, we develop semantic artifacts that support metadata disambiguation and interoperability, enabling seamless data reuse across projects. We create innovative tools for consistent metadata management, ensuring alignment with relevant standards. By developing course materials, offering training, and facilitating community exchanges, we raise awareness about the importance of effective metadata management, unlocking new opportunities within the scientific community and driving a cultural shift in how data and metadata are handled.
