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04.discussion.md

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Discussion

BrAPI for Breeders

While the BrAPI technical specification is designed to be read and used by software developers, its underlying purpose is to support the work of breeders and other scientists by making routine processes faster, easier, and cheaper. BrAPI offers a convenient path to automation, interoperability, and data integration for software tools in breeding, genetics, phenomics, and other related agricultural domains. By integrating the tools described above, breeders and scientists can spend less time on data management and more time focusing on science. For many, the ultimate goal is the development of a digital data ecosystem: a collection of software tools and applications that can all work together seamlessly. In this scenario, data is digitally collected, automatically sent to quality control systems, batch analyzed to provide actionable insights, and finally stored in accessible databases for long-term applications. As tools continue to adopt the BrAPI standard, this vision is beginning to approach reality.

Looking Ahead

The BrAPI project leadership and community are committed to building standards to support new use cases and technologies as they are adopted by breeders and other scientists, potentially including drone imaging data, spectroscopy, LIDAR, metabolomics, transcriptomics, agronomics, high-throughput phenotyping, pangenomics, and machine learning based analysis. Each of these technologies will have unique challenges, generate different types of data, and require substantial thought and discussion before being added to the BrAPI specification. This process has already begun for several data types, with small groups working to build generic data models and proposed communication standards. As these community efforts are completed, they will become part of a future version of the BrAPI standard, enabling further interoperability and simplifying data exchange.

Expanding the BrAPI specification is important for the community, but this growth should not reinvent or compete with existing functional standards. Additions to the BrAPI specification are reviewed thoroughly by the community to make sure BrAPI is compliant with existing standards and data structures. For example, the community has requested compliance with the GFF3 standard for genomic data and the GeoTIFF standard for aerial image data. Pieces of these existing popular data structures might be integrated into the overall BrAPI standard documentation. In some cases, BrAPI will only reference other standards instead of including them in the specification. For example, there have been community discussions around developing connections with the NOAA CDO standard for weather data or the Galaxy Analytics API for analytics pipeline controls and information. These standards are perfectly adequate on their own and recreating them in the BrAPI standard would be redundant.

Conclusion

The BrAPI project only exists because of the community of software engineers, biologists, and other scientists who support and use it. While there were many tools and use cases presented here, it is not an exhaustive list of all BrAPI-compliant systems. As long as the standard continues to be supported, the community will continue to expand. As more groups continue to make their tools BrAPI compliant, others will see the value in implementing BrAPI into their own tools, allowing the community to strengthen and grow. By providing an open standard for breeding data, and the infrastructure and community to support it, the BrAPI project is doing its part to support a productive agricultural system amidst the pressing challenges of climate change. If this manuscript is your first introduction to the BrAPI project, the authors invite you to join the community. More information is available at brapi.org.