Research Output per year
and knowledgebases). Wringing value from such databases depends on the discipline of data science and on
the humble bricks and mortar that make integration possible; identifiers are a core component of this
integration infrastructure. Drawing on our experience and on work by other groups, we outline ten lessons we
have learned about the identifier qualities and best practices that facilitate large-scale data integration.
Specifically, we propose actions that identifier practitioners (database providers) should take in the design,
provision and reuse of identifiers; we also outline important considerations for those referencing identifiers in
various circumstances, including by authors and data generators. While the importance and relevance of each
lesson will vary by context, there is a need for increased awareness about how to avoid and manage common
identifier problems, especially those related to persistence and web-accessibility/resolvability. We focus
strongly on web-based identifiers in the life sciences; however, the principles are broadly relevant to other
Identifiers for the 21st century: How to design, provision, and reuse persistent identifiers to maximize utility and impact of life science dataMcMurry, J. A., Juty, N., Blomberg, N., Burdett, T., Conlin, T., Conte, N., Courtot, M., Deck, J., Dumontier, M., Fellows, D. K., Gonzalez-Beltran, A., Gormanns, P., Grethe, J. S., Hastings, J., Heriche, J-K., Hermjakob, H., Ison, J. C., Jimenez, R. C., Jupp, S., Kunze, J. & 24 others, , Jun 2017, In : Plos Biology. 15, 6, e2001414.
Research output: Contribution to journal › Article › Academic › peer-review