Plant Science Data Integration, from Building Community Standards to Defining a Consistent Data Lifecycle - INRAE - Institut national de recherche pour l’agriculture, l’alimentation et l’environnement
Chapitre D'ouvrage Année : 2023

Plant Science Data Integration, from Building Community Standards to Defining a Consistent Data Lifecycle

Résumé

Abstract FAIR (Findable, Accessible, Interoperable, Reusable) data principles for plant research build upon experience from other life science domains such as genomics. But plant specificities, e.g. plant-environment interactions or phenotypes, require tailored solutions. Major global players have joined forces to answer that challenge with the Minimal Information About a Plant Phenotyping Experiment (MIAPPE, www.miappe.org ) that handles general metadata organization and its companion web service API, the Breeding API ( www.brapi.org ). Both rely on two established data standards, the MultiCrop Passport Descriptors (MCPD) for identification of plant genetic resources and the Crop Ontology ( www.cropontology.org ) for trait documentation. Researcher communities’ coordination and collaborative approaches have enabled the success and adoption of MIAPPE and led to a general data lifecycle description by ELIXIR Plant Sciences Community to identify gaps and needed developments. A priority has been placed on addressing the “first mile” of data publishing, i.e. the gathering and documentation of data by the researcher, which enables relevant data findability and reusability. Here we describe the existing ecosystem of tools and standards for plant scientists as well as their history, including their convergence through the use of MIAPPE for describing genotyping datasets.

Dates et versions

hal-03896793 , version 1 (13-12-2022)

Identifiants

Citer

Cyril Pommier, Frederik Coppens, Hanna Ćwiek-Kupczyńska, Daniel Faria, Sebastian Beier, et al.. Plant Science Data Integration, from Building Community Standards to Defining a Consistent Data Lifecycle. Towards Responsible Plant Data Linkage: Data Challenges for Agricultural Research and Development, Springer International Publishing, pp.149-160, 2023, ⟨10.1007/978-3-031-13276-6_8⟩. ⟨hal-03896793⟩
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