Applying FAIR Principles to Plant Phenotypic Data Management in GnpIS

Area of Science:

• Plant science
• Bioinformatics
• Data management

Background:

• Plant phenomics research generates vast datasets.
• Effective data management is crucial for scientific advancement.
• Existing repositories may lack flexibility or interoperability.

Purpose of the Study:

• Introduce GnpIS, a plant phenomics data repository.
• Highlight its adherence to FAIR data principles.
• Demonstrate its capacity for integrating diverse plant experimental data.

Main Methods:

• Developed a generic, ontology-driven data model.
• Implemented an innovative software architecture for data integration, storage, and querying.
• Leveraged international standards (Crop Ontology, MIAPPE, Breeding API).

Main Results:

• GnpIS provides long-term, FAIR access to plant phenomics data.
• The repository handles diverse species and experiment types, including environmental measures.
• Ensures data integration and interoperability with genotyping data.

Conclusions:

• GnpIS facilitates data sharing and reuse in plant science.
• Its compliance with standards enables interoperability with other repositories.
• Contributes to international federations of information systems for enhanced research.