We often say that “A is a version of B” but do not explain what we mean by “version”. We imply that B was somehow derived from A or that they share a common ancestor. But how is B related to A? How do they differ? Do they differ in content or format? What is the significance of this difference? While this sounds like a question about the provenance of a dataset, it goes beyond that and asks questions about the identity of a digital object and the intellectual and creative work it embodies.
The Research Data Alliance Data Versioning Working Group (https://www.rd-alliance.org/groups/data-versioning-ig/) collected over forty use cases of versioning practices for data and software and published a set of principles distilled from the group’s analysis of them. These Principles define terminology that helps us differentiate different types of versioning and thus allow us to address the use cases more precisely. In follow-up discussions, we learned that the Principles are too abstract to apply to the operation of data repositories or to guide the citation of digital resources. Therefore, this document aims to translate the Principles into actionable recommendations for data versioning.
https://doi.org/10.5281/zenodo.13743876
| Artificial Intelligence |
| Research Data Curation and Management Works |
| Digital Curation and Digital Preservation Works |
| Open Access Works |
| Digital Scholarship |
