Research Data Curation and Management Bibliography

This e-book includes over 800 selected English-language articles and books that are useful in understanding the curation of digital research data in academic and other research institutions. It covers topics such as research data creation, acquisition, metadata, provenance, repositories, management, policies, support services, funding agency requirements, open access, peer review, publication, citation, sharing, reuse, and preservation. It has live links to included works. Abstracts are included in this bibliography if a work is under certain Creative Commons Licenses. This book is licensed under a Creative Commons Attribution 4.0 International License. Cite as: Bailey, Charles W., Jr. Research Data Curation and Management Bibliography. Houston: Digital Scholarship, 2021

Manuel de préservation numérique

Deuxième édition révisée du manuel de préservation numériqueComprend des références bibliographiques et webographique

Assessing Migration Risk for Scientific Data Formats

The majority of information about science, culture, society, economy and the environment is born digital, yet the underlying technology is subject to rapid obsolescence. One solution to this obsolescence, format migration, is widely practiced and supported by many software packages, yet migration has well known risks. For example, newer formats – even where similar in function – do not generally support all of the features of their predecessors, and, where similar features exist, there may be significant differences of interpretation. There appears to be a conflict between the wide use of migration and its known risks. In this paper we explore a simple hypothesis – that, where migration paths exist, the majority of data files can be safely migrated leaving only a few that must be handled more carefully – in the context of several scientific data formats that are or were widely used. Our approach is to gather information about potential migration mismatches and, using custom tools, evaluate a large collection of data files for the incidence of these risks. Our results support our initial hypothesis, though with some caveats. Further, we found that writing a tool to identify “risky ” format features is considerably easier than writing a migration tool