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In the era of big data, keeping all data or copies of data unselectively has become unrealistic or unreasonable for many research organisations. Knowing what data to keep, how to store them and for how long is essential but can be challenging. Beyond the retention and disposal of research data mandated by legislation and funding bodies, suitable practices in research data retention and disposal can play a fundamental role in making data storage sustainable and ensuring that data remain valuable, authentic and compatible with the FAIR (Findable, Accessible, Interoperable, Reusable) and CARE (Collective benefit, Authority to control, Responsibility and Ethics) data principles. They also enhance the discoverability, sharing and reuse of research data. In this report, eight recommendations are proposed to provide microscopy research facilities with guidance and foster best practices in research data retention and disposal. These recommendations are based on a survey of the facilities on their awareness and practices in data retention and disposal, and focus on key elements: 1. data retention policy; 2. data disposal (after the retention of users’ data and suitable protocol for data elimination); 3. data security and access to users’ data; 4. storage of users’ data; 5. sustainable file formats for data retention; 6. metadata collection; and 7. research data management planning. This work was undertaken under Work Package 4: “Big-data electron and correlative microscopy from instrument to publication” of the Australian Characterisation Commons at Scale (ACCS) project.
FAIR data, Best practices, Metadata, Sustainable data storage, CARE data, Australian Characterisation Commons at Scale (ACCS)
FAIR data, Best practices, Metadata, Sustainable data storage, CARE data, Australian Characterisation Commons at Scale (ACCS)
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| 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 |
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