Why we ditched shiny in favour of react
When is it time to ditch the known tech stack and embrace something new? For ESR’s data science team, the pandemic forced us to develop advanced geospatial analysis tools at pace. We pushed the limits of the likes of R shiny, and while toolkits like {golem} helped us to build production grade dashboards, we found that our ambitions were limited by the frameworks.
More recently, we’ve settled on the React framework for advanced applications. In this presentation, Richard will present several use cases which were simplified through the adaptation of React.
Examples will include:
- deploying machine learning to web browsers, and benchmarking performance
- the integration of large language models into ESR’s digital twin
- new ways to visualise agent based models using Cesium
- recharts and d3 for interactive graphs and process visualisation
- how we’re using libraries such as immer and zustand to maintain state
- how we’re using react, express and sequelize to build standalone APIs
- how we build and deploy react apps
To conclude, we will argue that React offers a simple and flexible option to develop and deploy advanced AI powered data visualisation tools – and, as such, it deserves a higher profile in the eResearch community.
ABOUT THE AUTHOR
Richard Dean is a senior data scientist in ESR's core data science team. He has over 20 years’ experience working with health, forensic and environmental data sets, specialising in the development of novel data tools and visualisation techniques. He currently leads a research programme looking at the use of computer vision for rapid diagnostics and is responsible for the development of ESR's digital twin user interface.
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For more information about the eResearch NZ / eRangahau Aotearoa conference, visit:
https://eresearchnz.co.nz/
