Standards for distributed Plant Phenotyping data integration: challenges and solutions.

Cyril Pommier (1, 2)

1 URGI - Unité de Recherche Génomique Info
2 Université Paris-Saclay

Plant Phenotyping data management following the FAIR principles (Findable, Accessible, Interoperable, Resusable) is highly challenging because of its heterogeneity. Thus, simply integrating and consolidating data within a single dataset like a phenotyping network is already a complicated task which is even more complex when trying to link different datasets together for long term data reuse. The Minimal Information About Plant Phenotyping Experiment (MIAPPE) data standard have been built to answer this challenge. It is s included in several systems including production databases like PHIS, data repositories like GnpIS or eDale, file formats like ISA Tab, and in a web service, the Breeding API. This enables interoperability in a growing list of tools and databases. We will review those implementations and their benefits, show its current adoption state and detail the future plans for phenotyping data standard.

Mots clés: standard; ontologies; phenotyping; information system; semantic

Domaines: Biologie végétale; Bio-informatique [q-bio.QM]; Web

Cyril Pommier. Standards for distributed Plant Phenotyping data integration: challenges and solutions.. COST FA1306 "The quest for tolerant varieties - Phenotyping at plant and cellular level" - WG1 Meeting "Phenotyping: from the lab to the field", Mar 2018, Leuven, Belgium. pp.67 slides. ⟨hal-01779751⟩