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Dzale Yeumo E, Alaux M, Arnaud E, et al. Developing data interoperability using standards: A wheat community use case. F1000Res. 2017;6:1843doi: 10.12688/f1000research.12234.2.
Dzale Yeumo, E., Alaux, M., Arnaud, E., Aubin, S., Baumann, U., Buche, P., Cooper, L., Ćwiek-Kupczyńska, H., Davey, R. P., Fulss, R. A., Jonquet, C., Laporte, M. A., Larmande, P., Pommier, C., Protonotarios, V., Reverte, C., Shrestha, R., Subirats, I., Venkatesan, A., Whan, A., & Quesneville, H. (2017). Developing data interoperability using standards: A wheat community use case. F1000Research, 61843. https://doi.org/10.12688/f1000research.12234.2
Dzale Yeumo, Esther, et al. "Developing data interoperability using standards: A wheat community use case." F1000Research vol. 6 (2017): 1843. doi: https://doi.org/10.12688/f1000research.12234.2
Dzale Yeumo E, Alaux M, Arnaud E, Aubin S, Baumann U, Buche P, Cooper L, Ćwiek-Kupczyńska H, Davey RP, Fulss RA, Jonquet C, Laporte MA, Larmande P, Pommier C, Protonotarios V, Reverte C, Shrestha R, Subirats I, Venkatesan A, Whan A, Quesneville H. Developing data interoperability using standards: A wheat community use case. F1000Res. 2017 Oct 16;6:1843. doi: 10.12688/f1000research.12234.2. eCollection 2017. PMID: 29333241; PMCID: PMC5747345.
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F1000Res. 2017 Oct 16;6:1843. doi: 10.12688/f1000research.12234.2. eCollection 2017.

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

F1000Research

Esther Dzale Yeumo, Michael Alaux, Elizabeth Arnaud, Sophie Aubin, Ute Baumann, Patrice Buche, Laurel Cooper, Hanna Ćwiek-Kupczyńska, Robert P Davey, Richard Allan Fulss, Clement Jonquet, Marie-Angélique Laporte, Pierre Larmande, Cyril Pommier, Vassilis Protonotarios, Carmen Reverte, Rosemary Shrestha, Imma Subirats, Aravind Venkatesan, Alex Whan, Hadi Quesneville

Affiliations

  1. INRA, UAR 1266 DIST Délégation Information Scientifique et Technique, Centre de recherche Ile-de-France-Versailles-Grignon, Versailles, 78000 , France.
  2. Unité de Recherche Génomique-Info (URGI), INRA, Université Paris-Saclay, Versailles, 78026, France.
  3. Bioversity International, Montpellier, 34397, France.
  4. School of Agriculture, Food and Wine, University of Adelaide, Glen Osmond, SA, 5064, Australia.
  5. Institut National de la Recherche Scientifique, Centre National De La Recherche Scientifique, Montpellier, 34000, France.
  6. Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR, 97331, USA.
  7. Department of Biometry and Bioinformatics, Institute of Plant Genetics, Polish Academy of Sciences, Pozna?, 60-479, Poland.
  8. Earlham Institute , Norwich, NR4 7UZ, UK.
  9. International Maize and Wheat Improvement Center, Texcoco, 56237, Mexico.
  10. Center for Biomedical Informatics Research, Stanford University, Stanford, CA, 94305, USA.
  11. Laboratory of Informatics, Robotics and Microelectronics of Montpellier , University of Montpellier, Montpellier, 34090, France.
  12. Institut de Biologie Computationnelle, Université Montpellier, Montpellier, 34090, France.
  13. Institut de Recherche pour le Développement , Marseille, 13572, France.
  14. NEUROPUBLIC S.A., Piraeus, GR18545, Greece.
  15. IRTA. Ctra. de Poble Nou, Sant Carles de la Ràpita, E-43540, Spain.
  16. Food and Agriculture Organization of the United Nations, Rome, 00153, Italy.
  17. Commonwealth Science and Industrial Research Organisation, Agriculture and Food, Canberra, ACT, 2601, Australia.

PMID: 29333241 PMCID: PMC5747345 DOI: 10.12688/f1000research.12234.2

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.

Keywords: bio-ontologies; data formats; data interoperability; metadata; ontology repository; standard vocabularies; wheat

Conflict of interest statement

No competing interests were disclosed.

References

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