Evidence map›Paper›PMID 29333241›Full record

ArticleF1000Research2017

Developing data interoperability using standards: A wheat community use case.

Esther Dzale Yeumo, Michael Alaux, Elizabeth Arnaud, Sophie Aubin, Ute Baumann, Patrice Buche, Laurel Cooper, Hanna Ćwiek-Kupczyńska, Robert P Davey, Richard Allan Fulss and 11 more

Abstract read
In one paragraph

Article in F1000Research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. GrainGenes: centralized small grain resources and digital platform for geneticists and breeders.Database : the journal of biological databases and curation · 2019
    Article
  8. 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

21 authors.

Esther Dzale YeumoINRA, UAR 1266 DIST Délégation Information Scientifique et Technique, Centre de recherche Ile-de-France-Versailles-Grignon, Versailles, 78000 , France.
Michael AlauxUnité de Recherche Génomique-Info (URGI), INRA, Université Paris-Saclay, Versailles, 78026, France.ORCID https://orcid.org/0000-0001-9356-4072
Elizabeth ArnaudBioversity International, Montpellier, 34397, France.
Sophie AubinINRA, UAR 1266 DIST Délégation Information Scientifique et Technique, Centre de recherche Ile-de-France-Versailles-Grignon, Versailles, 78000 , France.
Ute BaumannSchool of Agriculture, Food and Wine, University of Adelaide, Glen Osmond, SA, 5064, Australia.
Patrice BucheInstitut National de la Recherche Scientifique, Centre National De La Recherche Scientifique, Montpellier, 34000, France.
Laurel CooperDepartment of Botany and Plant Pathology, Oregon State University, Corvallis, OR, 97331, USA.ORCID https://orcid.org/0000-0002-6379-8932
Hanna Ćwiek-KupczyńskaDepartment of Biometry and Bioinformatics, Institute of Plant Genetics, Polish Academy of Sciences, Poznań, 60-479, Poland.
Robert P DaveyEarlham Institute , Norwich, NR4 7UZ, UK.ORCID https://orcid.org/0000-0002-5589-7754
Richard Allan FulssInternational Maize and Wheat Improvement Center, Texcoco, 56237, Mexico.
Clement JonquetCenter for Biomedical Informatics Research, Stanford University, Stanford, CA, 94305, USA.ORCID https://orcid.org/0000-0002-2404-1582
Marie-Angélique LaporteBioversity International, Montpellier, 34397, France.
Pierre LarmandeInstitut de Biologie Computationnelle, Université Montpellier, Montpellier, 34090, France.ORCID https://orcid.org/0000-0002-2923-9790
Cyril PommierUnité de Recherche Génomique-Info (URGI), INRA, Université Paris-Saclay, Versailles, 78026, France.ORCID https://orcid.org/0000-0002-9040-8733
Vassilis ProtonotariosNEUROPUBLIC S.A., Piraeus, GR18545, Greece.ORCID https://orcid.org/0000-0001-8534-0546
Carmen ReverteIRTA. Ctra. de Poble Nou, Sant Carles de la Ràpita, E-43540, Spain.ORCID https://orcid.org/0000-0003-4768-7180
Rosemary ShresthaInternational Maize and Wheat Improvement Center, Texcoco, 56237, Mexico.
Imma SubiratsFood and Agriculture Organization of the United Nations, Rome, 00153, Italy.
Aravind VenkatesanInstitut de Biologie Computationnelle, Université Montpellier, Montpellier, 34090, France.ORCID https://orcid.org/0000-0003-4019-1940
Alex WhanCommonwealth Science and Industrial Research Organisation, Agriculture and Food, Canberra, ACT, 2601, Australia.
Hadi QuesnevilleUnité de Recherche Génomique-Info (URGI), INRA, Université Paris-Saclay, Versailles, 78026, France.ORCID https://orcid.org/0000-0003-3001-4908

Funding

Biotechnology and Biological Sciences Research Council BBS/E/T/000PR9817
6 · The paper itself

Abstract

In this article, we present a joint effort of the wheat research community, along with data and ontology experts, to develop wheat data interoperability guidelines. Interoperability is the ability of two or more systems and devices to cooperate and exchange data, and interpret that shared information. Interoperability is a growing concern to the wheat scientific community, and agriculture in general, as the need to interpret the deluge of data obtained through high-throughput technologies grows. Agreeing on common data formats, metadata, and vocabulary standards is an important step to obtain the required data interoperability level in order to add value by encouraging data sharing, and subsequently facilitate the extraction of new information from existing and new datasets. During a period of more than 18 months, the RDA Wheat Data Interoperability Working Group (WDI-WG) surveyed the wheat research community about the use of data standards, then discussed and selected a set of recommendations based on consensual criteria. The recommendations promote standards for data types identified by the wheat research community as the most important for the coming years: nucleotide sequence variants, genome annotations, phenotypes, germplasm data, gene expression experiments, and physical maps. For each of these data types, the guidelines recommend best practices in terms of use of data formats, metadata standards and ontologies. In addition to the best practices, the guidelines provide examples of tools and implementations that are likely to facilitate the adoption of the recommendations. To maximize the adoption of the recommendations, the WDI-WG used a community-driven approach that involved the wheat research community from the start, took into account their needs and practices, and provided them with a framework to keep the recommendations up to date. We also report this approach's potential to be generalizable to other (agricultural) domains.

Indexed as

bio-ontologiesdata formatsdata interoperabilitymetadataontology repositorystandard vocabularieswheat

Identifiers

PMID29333241
PMCPMC5747345

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.