Measures for interoperability of phenotypic data: minimum information requirements and formatting.

Area of Science:

• Plant Science
• Bioinformatics
• Data Management

Background:

• Plant phenotypic data holds valuable information for understanding life mechanisms.
• Phenotyping experiments are complex and time-consuming, necessitating data reuse for scientific advancement.
• Lack of standardized metadata hinders data interpretation, replicability, comparability, and interoperability.

Purpose of the Study:

• To propose guidelines for describing plant phenotyping experiments.
• To establish standards for metadata content and formatting to facilitate data exchange.
• To promote findable, accessible, interoperable, and reusable (FAIR) data in plant phenotyping.

Main Methods:

• Development of the "Minimum Information About a Plant Phenotyping Experiment" (MIAPPE) document.
• Creation of a Phenotyping Configuration for the ISA-Tab format for practical data organization.
• Demonstration with examples of ISA-Tab-formatted phenotypic data and implemented systems.

Main Results:

• Proposed MIAPPE guidelines specify essential information for plant phenotyping experiments.
• ISA-Tab format with Phenotyping Configuration provides a practical structure for organizing metadata.
• Examples illustrate the application of the proposed standards in real-world systems.

Conclusions:

• Adoption of these standards will enhance the findability, accessibility, interoperability, and reusability of plant phenotyping data.
• Standardized metadata is essential for maximizing the value of plant phenotypic datasets.
• This work aims to foster collaboration and accelerate discoveries in plant science through improved data practices.