Every minute, satellites and sensors all around Aotearoa are taking all kinds of measurements – images, temperatures, water flows, weather conditions, you name it – and pinging this information to servers.
For environmental researchers, these data hold the clues for what is coming next, but when there is so much information how do you make sense of it all?
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The data science programme TAIAO aims to help with this.
Led by the University of Waikato, the TAIAO team is developing new machine learning methods able to deal with large quantities of environmental data.
Funded by the Ministry of Business, Innovation and Employment to the tune of $13 million over seven years, the programme is building an open-source online framework to allow researchers to share machine learning algorithms, tweaks and datasets.
It’s a collaboration across the Universities of Waikato, Auckland and Canterbury as well as engineering companies Beca and MetService.
Environmental scientists, such as Professor Karin Bryan, help connect data scientists and data engineers to interesting New Zealand-specific datasets and problems to tackle.
Then data scientists, such as Dr Nick Lim, create and optimise machine learning algorithms to make relevant predictions, and then make these available online for other environmental researchers to use and adjust as they need.
In this way, the TAIAO team aim to promote a vibrant community of environmental researchers sharing information aimed at getting reliable answers or predictions that can guide good decision-making.
