Project
Data Science for Climate Adaptation (Postdoc project - Anne Sietsma)
This research is part of a larger interdisciplinary project to investigate how data science methods can help us adapt to the risks of climate change. Countries and communities are increasingly taking such adaptation actions. But tracking these actions is difficult as this information is scattered across many reports, websites and articles. Using Artificial Intelligence, we can work with such diverse data to show how much more needs to be done, where more attention is most needed and what works already.
Background
As the impacts of climate change are becoming clearer and more severe, adaptation is increasingly crucial. Adaptation refers to taking action to minimise the risks of climate change. To adapt effectively, we need to know both what works and what has already been done. However, the effects of climate change are very different around the world: some countries will see more floods while others see droughts; some communities can afford to invest in big and expensive projects while others cannot. Adaptation can also take place at very different scales – from individuals to communities to whole countries and even international projects. As a result of all this diversity, it is difficult to track where and when adaptation is taking place.
Project description
The project ‘Data Driven Discoveries in a Changing Climate’ explores solutions to this challenge using modern data science methods, especially recent advances in Artificial Intelligence (AI). Such methods can handle large diverse datasets and they can be trained to make relatively fine-grained distinctions. As part of this project, the Public Administration and Policy group is focusing on using AI to map and monitor adaptation solutions by collecting and analysing large datasets of texts, including for example government websites, scientific publications and legal documents.