Applying FAIR Principles to Plant Phenotypic Data Management in GnpIS

Abstract

GnpIS is a data repository for plant phenomics that stores whole field and greenhouse experimental data including environment measures. It allows long-term access to datasets following the FAIR principles: Findable, Accessible, Interoperable, and Reusable, by using a flexible and original approach. It is based on a generic and ontology driven data model and an innovative software architecture that uncouples data integration, storage, and querying. It takes advantage of international standards including the Crop Ontology, MIAPPE, and the Breeding API. GnpIS allows handling data for a wide range of species and experiment types, including multiannual perennial plants experimental network or annual plant trials with either raw data, i.e., direct measures, or computed traits. It also ensures the integration and the interoperability among phenotyping datasets and with genotyping data. This is achieved through a careful curation and annotation of the key resources conducted in close collaboration with the communities providing data. Our repository follows the Open Science data publication principles by ensuring citability of each dataset. Finally, GnpIS compliance with international standards enables its interoperability with other data repositories hence allowing data links between phenotype and other data types. GnpIS can therefore contribute to emerging international federations of information systems.

Plant phenotyping relevance

植物フェノミクスデータリポジトリの設計・標準化・相互運用性を扱う方法論的研究であり、フェノタイピングデータ基盤が中心です。

Code and data availability

This is an infrastructure/data-management paper describing the GnpIS phenotyping repository rather than a single measurement study. The paper-specific public assets are the GnpIS repository itself (hosting the curated phenotyping trial datasets the paper describes), the authors' public ontology versioning repository on