M3.4 Defining PID Practices in FAIR data management
Creators
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1.
CSC - IT Center for Science (Finland)
Description
Taking PIDs into use is not a very cumbersome nor difficult task in itself, however, applying good practices for PID implementation e.g. for a particular workflow or when working with a particular type of data, is not a self-evident task and is in need of further well-tested documentation. This milestone report highlights a first set of descriptions on good practices for implementing PIDs in FAIR data management, as well as plans for the immediate future, as defined by eight use case partners representing different scientific disciplines. The documentation on best practices around PID minting practices is defined for different types of datasets, workflows and research objects, leading to more exact data citation and a broader and more targeted use of PIDs. The PID practices will be explored from the viewpoint of PIDs in data production workflows, PIDs in complex data citation and PIDs for sensitive data. Advancing machine-actionability, scientific reproducibility and research object type definitions when managing PIDs are also within the scope of this work and will provide a nuanced discussion on best practice implementation of PIDs. The lessons learned from this work will be translated across research domains to serve the broader research community and ultimately foster harmonised PID practices.
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MS3.4 Defining PID practices in FAIR data management_FAIR-IMPACT_20231123_v1.0.pdf
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(473.9 kB)
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