InfraStructure for dAta-BasEd Learning in environmental sciences (ISABEL)

• Applicants: Professor Dr. Achim Streit; Professor Dr.-Ing. Erwin Zehe
• Subject Area: Data Management, Data-Intensive Systems, Computer Science Methods in Business Informatics ; Hydrogeology, Hydrology, Limnology, Urban Water Management, Water Chemistry, Integrated Water Resources Management
• Term: since 2022
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 496155047

The amount and diversity of digitally available environmental data is continuously increasing. However, they are often hardly accessible or scientifically usable. The datasets frequently lack sufficient metadata description, are stored in a variety of data formats, and are still saved on local storage devices instead of data portals or repositories. Based on the virtual research environment V-FOR-WaTer, which was developed in a previous project, ISABEL aims at making this data abundance available in an easy-to-use web portal. Environmental scientists get access to data from different sources, e.g. state offices or university projects, and can share their own data through the portal. Integrated tools help to easily pre-process and scale the data and make them available in a consistent format. Further tools for more complex scientific analyses will be included. These are both implemented by the developers of the portal according to the requirements of the scientific community and contributed directly by the portal’s users. The possibility to store workflows together with the tools and respective data ensures reproducible data analysis. Additionally, interfaces with existing data repositories enable easy publication of the scientists’ data directly from the portal. ISABEL addresses the needs of researchers of hydrology and environmental science to not only find and access datasets but also conduct efficient data-based learning with standardised tools and reproducible workflows.

• DFG Programme: Research data and software (Scientific Library Services and Information Systems)
• Co-Investigators: Dr. Sibylle Haßler; Dr. Jörg Meyer; Dr. Marcus Strobl