Data Science of the Natural Environment: A Research Roadmap
Data Science of the Natural Environment: A Research Roadmap
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DOI：
10.3389/fenvs.2019.00121
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发表时间：
2019-08-14
影响因子：
4.6
通讯作者：
Young, Paul J.
中科院分区：
文献类型：
--
作者：
Blair, Gordon S.;Henrys, Peter;Young, Paul J.
数据科学是从潜在的复杂数据中提取意义的科学。这是一个快速发展的领域，从包括计算机科学、统计学和复杂性科学在内的多个不同学科领域汲取原理和技术。数据科学正在对商业、健康和智慧城市等多个领域产生深远影响。本文认为，数据科学可以在地球和环境科学领域产生同等或更大的影响，提供丰富的新技术，以支持对自然环境及其所有复杂性的更深入了解，以及针对气候变化制定有充分依据的缓解和适应战略。本文认为，针对自然环境的数据科学给数据科学带来了新的挑战，特别是在复杂性、空间和时间推理以及管理不确定性方面。本文还描述了环境数据科学的一个案例研究，它为该领域的前景提供了见解。论文最后提出了一份研究路线图，强调了环境数据科学面临的10大挑战，并邀请他们成为国际社会的一部分，共同努力解决这些问题。
Data science is the science of extracting meaning from potentially complex data. This is a fast moving field, drawing principles and techniques from a number of different disciplinary areas including computer science, statistics and complexity science. Data science is having a profound impact on a number of areas including commerce, health, and smart cities. 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. 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. The paper also describes a case study in environmental data science which offers up insights into the promise of the area. 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.