Hollaway Michael J, Dean Graham, Blair Gordon S, Brown Mike, Henrys Peter A, Watkins John
UK Centre for Ecology and Hydrology, Lancaster Environment Centre, Lancaster, UK.
School of Computing and Communications, Lancaster University, Lancaster, UK.
Patterns (N Y). 2020 Sep 17;1(7):100103. doi: 10.1016/j.patter.2020.100103. eCollection 2020 Oct 9.
In recent years, there has been a drive toward more open, cross-disciplinary science taking center stage. This has presented a number of challenges, including providing research platforms for collaborating scientists to explore big data, develop methods, and disseminate their results to stakeholders and decision makers. We present our vision of a "data science lab" as a collaborative space where scientists (from different disciplines), stakeholders, and policy makers can create data-driven solutions to environmental science's grand challenges. We set out a clear and defined research roadmap to serve as a focal point for an international research community progressing toward a more data-driven and transparent approach to environmental data science, centered on data science labs. This includes ongoing case studies of good practice, with the infrastructural and methodological developments required to enable data science labs to support significant increase in our cross- and trans-disciplinary science capabilities.
近年来，一直存在着一种推动更开放、跨学科科学成为核心的趋势。这带来了诸多挑战，包括为合作科学家提供研究平台，以探索大数据、开发方法，并将其成果传播给利益相关者和决策者。我们提出了“数据科学实验室”的愿景，将其作为一个协作空间，科学家（来自不同学科）、利益相关者和政策制定者可以在此创建以数据驱动的解决方案，应对环境科学的重大挑战。我们制定了清晰明确的研究路线图，作为国际研究团体的焦点，朝着以数据科学实验室为核心、更以数据为驱动且透明的环境数据科学方法迈进。这包括正在进行的良好实践案例研究，以及数据科学实验室为大幅提升我们的跨学科和多学科科学能力所需的基础设施和方法发展。
