<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>
The Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) is a leading international plant science institute specialising in biodiversity and plant performance research. Under the leadership of a team of data stewards, a research and laboratory information system (RALIMS) was introduced in 2011 as the result of a concept study as an infrastructure that serves as a scalable and sustainable general data management service in compliance to the FAIR criteria. The prioritisation of a participatory approach was a key lesson, and the need for a common language between the laboratory, scientists and bioinformaticians was the next. Fluctuating personnel resource had to be addressed in a flexible way as well. Futhermore, well-chosen pilot working groups helped to increase the acceptance of necessary research data management work by the majority of colleagues. The next lesson learnt was the importance of an indivudial customisable front-end layout and data import interfaces to the respective needs of the data curators. Last but not least, agile training concepts and formats are also of great importance.
Working with challenging data: Data on a large scale: big data or large collections of long-tail data, IDCC25, Sustainability and strategy: Work on curation processes, techniques, costs, and workflows, Sustainability, Papers, Training concepts and formats, LIMS, Curation infrastructure: Proposals for new approaches to large-scale service delivery, Curation infrastructure: Tools, systems and services that are in development, Research Data Management Infrastructure, Working with challenging data: Complex data, models and formats, Education and training: How effective is current training in delivering knowledge and skills?
Working with challenging data: Data on a large scale: big data or large collections of long-tail data, IDCC25, Sustainability and strategy: Work on curation processes, techniques, costs, and workflows, Sustainability, Papers, Training concepts and formats, LIMS, Curation infrastructure: Proposals for new approaches to large-scale service delivery, Curation infrastructure: Tools, systems and services that are in development, Research Data Management Infrastructure, Working with challenging data: Complex data, models and formats, Education and training: How effective is current training in delivering knowledge and skills?
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |