Firstly, studies of the natural environment are increasingly data rich with a pressing need for new techniques to make sense of the accelerating amount of data being captured about environmental facets and processes. To date, there has been little work on data science applied to the understanding and management of the natural environment. The paper concludes with a research roadmap highlighting 10 top challenges of environmental data science and also an invitation to become part of an international community working collaboratively on these problems.ĭata science is emerging as a major new area of study, having significant impacts on areas as diverse as eCommerce and marketing, smart cities, logistics and transport, and health and well-being ( Dhar, 2013 Provost and Fawcett, 2013). The paper also describes a case study in environmental data science which offers up insights into the promise of the area. The paper argues that data science for the natural environment brings about new challenges for data science, particularly around complexity, spatial and temporal reasoning, and managing uncertainty. This paper argues that data science can have an equal if not greater impact in the area of earth and environmental sciences, offering a rich tapestry of new techniques to support both a deeper understanding of the natural environment in all its complexities, as well as the development of well-founded mitigation and adaptation strategies in the face of climate change. Data science is having a profound impact on a number of areas including commerce, health, and smart cities. This is a fast moving field, drawing principles and techniques from a number of different disciplinary areas including computer science, statistics and complexity science.
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