Data management in balance - a decade of balancing pragmatism, sustainability and innovation at plant research center IPK Gatersleben
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Summary
This summary is machine-generated.IPK Gatersleben established a sustainable research data management (RDM) infrastructure over 15 years, prioritizing data accessibility and long-term preservation. This involved creating robust RDM processes, infrastructure, and governance, ensuring compliance with FAIR data principles.
Area Of Science
- Plant science research
- Genetics and crop plant research
- Biodiversity studies
Background
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben has focused on biodiversity and crop plant performance.
- Over the past decade, IPK integrated research data lifecycle management with IT, standardization, and sustainable research data management (RDM) processes.
Purpose Of The Study
- To discuss the successes and challenges of operating a central RDM infrastructure over 15 years.
- To present measures for agile requirements engineering, technical and organizational implementation, governance, training, and roll-out of RDM.
- To highlight the benefits of a participatory approach in RDM implementation.
Main Methods
- Establishing a research data infrastructure, process landscape, capacity building, and governance structures.
- Implementing an ambidextrous approach to data management, balancing operational needs with agile adoption of innovations.
- Utilizing pilot working groups and data management champions for a participatory approach.
Main Results
- A generic research data infrastructure was created, archiving data accessibly and sustainably, predating FAIR criteria.
- Successful implementation of RDM processes, infrastructure, and governance.
- Demonstrated benefits of a participatory approach involving diverse personnel and researcher profiles.
Conclusions
- A 15-year experience in operating a central RDM infrastructure provides valuable insights into best practices.
- An ambidextrous RDM approach enables efficient compliance with FAIR criteria while embracing innovation.
- Sustainable RDM practices are crucial for good scientific practice and long-term data preservation.