Paul Shaw
Dr. Paul Shaw is a Senior Research Scientist and bioinformatician at The James Hutton Institute and the International Barley Hub. He leads the development of information systems for plant genetic resources, focusing on pragmatic data visualization to transform large-scale genomic and phenotypic data into accessible, interactive tools. Dr. Shaw is the lead developer of major platforms, including the open-source database Germinate and the pedigree visualization tool Helium. He also champions efficient data gathering via mobile applications like GridScore. Collaborating with international initiatives like the Global Crop Diversity Trust and DivSeek, his work integrates FAIR data principles into agricultural workflows, supporting global crop resilience and food security.
From Bits to Bites (and maybe some drinking too…)
Section titled “From Bits to Bites (and maybe some drinking too…)”Plant science is driven by increasingly complex experiments generating a wide diversity of data types. This data ranges from where a seed is stored to complex genotypic and trials data - and everything in between. Effectively harnessing this data requires robust data integration, storage and visualization tools that can transform raw experimental data into accessible, actionable insights for global breeding, experimental genetics and genebank communities.
This talk will explore some of the software tools developed at the James Hutton Institute/International Barley Hub to try and help us make sense of our data. Our solutions sit at the critical intersection of software development and plant sciences, focusing on the deployment of a common scalable, open source, and plant science focussed informatics infrastructure and tools. Software like Germinate [1] for storing and accessing experimental data, Helium [2] for visualizing complex pedigrees, and GridScore [3] for streamlining in-field data collection, have been at the core of our activities. In this talk we describe the processes undertaken in the development of our software tools and how they have been utilised by Hutton and international PGR projects. Finally, we look at how we aim to integrate AI into our barley science and PGR management at Hutton and highlight our strategic partnerships and ongoing international initiatives. We will examine how emerging AI-aided analyses are being seamlessly integrated into established tools to maximise the impact of agricultural data worldwide and how these can improve, develop and expand our established software foundation.
