Evidence map›Paper›PMID 25901117›Full record

ArticleZooKeys2015

Community next steps for making globally unique identifiers work for biocollections data.

Robert P Guralnick, Nico Cellinese, John Deck, Richard L Pyle, John Kunze, Lyubomir Penev, Ramona Walls, Gregor Hagedorn, Donat Agosti, John Wieczorek and 2 more

Abstract read
In one paragraph

Article in ZooKeys, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. The NCBI BioCollections Database.Database : the journal of biological databases and curation · 2018
    Article
  13. Article
  14. Article
  15. DNA barcoding and taxonomy: dark taxa and dark texts.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2016
    Review
  16. Article
  17. The importance of digitized biocollections as a source of trait data and a new VertNet resource.Database : the journal of biological databases and curation · 2016
    Article
  18. Article
  19. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Robert P GuralnickFlorida Museum of Natural History, University of Florida, Gainesville, FL 32611-2710 USA.
Nico CellineseFlorida Museum of Natural History, University of Florida, Gainesville, FL 32611-2710 USA.
John DeckBerkeley Natural History Museums, University of California, Berkeley, California, USA.
Richard L PyleDepartment of Natural Sciences, Bernice P. Bishop Museum, Honolulu, HI USA 96817.
John KunzeCalifornia Digital Library, University of California Office of the President, Oakland, CA USA.
Lyubomir PenevInstitute of Biodiversity and Ecosystem Research, Bulgarian Academy of Sciences, and Pensoft Publishers, Sofia, Bulgaria.
Ramona WallsiPlant Collaborative, University of Arizona,Tucson, AZ 85721.
Gregor HagedornMuseum für Naturkunde, Leibniz-Institut für Evolutions- und Biodiversitätsforschung, Invalidenstraße 43, 10115 Berlin, Germany.
Donat AgostiPlazi, Zinggstrasse 16, 3007 Bern, Switzerand.
John WieczorekMuseum of Vertebrate Zoology, University of California, Berkeley, CA USA. United States of America. 94720-3160.
Terry CatapanoPlazi, Zinggstrasse 16, 3007 Bern, Switzerand.
Roderic D M PageInstitute of Biodiversity, Animal Health and Comparative Medicine, College of Medical, Veterinary and Life Sciences, University of Glasgow Glasgow, G12 8QQ. UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Biodiversity data is being digitized and made available online at a rapidly increasing rate but current practices typically do not preserve linkages between these data, which impedes interoperation, provenance tracking, and assembly of larger datasets. For data associated with biocollections, the biodiversity community has long recognized that an essential part of establishing and preserving linkages is to apply globally unique identifiers at the point when data are generated in the field and to persist these identifiers downstream, but this is seldom implemented in practice. There has neither been coalescence towards one single identifier solution (as in some other domains), nor even a set of recommended best practices and standards to support multiple identifier schemes sharing consistent responses. In order to further progress towards a broader community consensus, a group of biocollections and informatics experts assembled in Stockholm in October 2014 to discuss community next steps to overcome current roadblocks. The workshop participants divided into four groups focusing on: identifier practice in current field biocollections; identifier application for legacy biocollections; identifiers as applied to biodiversity data records as they are published and made available in semantically marked-up publications; and cross-cutting identifier solutions that bridge across these domains. The main outcome was consensus on key issues, including recognition of differences between legacy and new biocollections processes, the need for identifier metadata profiles that can report information on identifier persistence missions, and the unambiguous indication of the type of object associated with the identifier. Current identifier characteristics are also summarized, and an overview of available schemes and practices is provided.

Indexed as

Biocollectionsfield collectionsGlobally Unique IdentifiersGUIDsidentifierslegacy collectionslinked open datasemantic publishing

Identifiers

PMID25901117
PMCPMC4400380

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.