Core Project 4 - Exploratories for large-scale and long-term functional biodiversity research - Central Data Management

• Applicant: Professorin Dr. Birgitta König-Ries
• Subject Area: Ecology and Biodiversity of Plants and Ecosystems ; Data Management, Data-Intensive Systems, Computer Science Methods in Business Informatics
• Term: since 2011
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 193925721

The importance of data and its reuse in synthesis and long-term studies is undisputed in the Biodiversity Exploratories programme. From the very beginning of the programme, a data policy was adopted, and a central database was implemented. This early focus on data management, including active curation and a consistent, user-driven approach to the topic, has led to high acceptance. The central database provides an environment for data exchange and easy reuse, thereby stimulating and supporting synthesis work. It offers tool support for different target groups: local management teams and the central project office use it for fieldwork administration and general information provision, while researchers benefit from tools such as the calculation of the LUI, an index for land-use intensity. At the same time, the database ensures data interpretability and supports quality control. Since 2021, the BEXIS2 software has been used for this purpose, supplemented by custom-developed modules. This proposal aims to ensure the continuation of these essential and successful activities for the Biodiversity Exploratories. In addition to providing infrastructure and user support, the focus will be on the following topics: the development of further research-supporting tools, the continued enhancement of data and repository FAIRness, including the increased integration of persistent identifiers, and the creation of data management plans for all funded projects. A significant emphasis will also be placed on dataset curation and the development of tools and workflows to support it. Additionally, modern generative AI approaches will be explored to improve data management, such as the automated capture of metadata.

• DFG Programme: Infrastructure Priority Programmes
• Subproject of: SPP 1374: Biodiversity Exploratories