Data-Intensive Ecological Research Is Catalyzed by Open Science and Team Science
Data-Intensive Ecological Research Is Catalyzed by Open Science and Team Science
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DOI：
10.1093/biosci/biy097
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发表时间：
2018-10-01
期刊：
影响因子：
10.1
通讯作者：
Soranno, Patricia A.
中科院分区：
文献类型：
--
作者：
Cheruvelil, Kendra Spence;Soranno, Patricia A.
社会和环境面临的许多问题需要生态学家使用越来越大的数据量和不同类型的数据，以及旨在利用这些数据的方法--也就是数据密集型科学。在本文中，我们认为数据密集型科学在与开放科学和团队科学相结合时将是最成功的。然而，在生态学中采用每一种类型的科学都存在文化障碍。我们描述了每种类型的科学的好处和存在的文化障碍，以及通过实践团队科学和开放科学与数据密集型科学相结合实现的强大协同效应。最后，我们建议每种类型的科学由无数实践组成，这些实践可以沿着从低到高采用水平的梯度进行调整，并倡导逐步采用每种类型的科学，以满足项目和研究人员的需求。
Many problems facing society and the environment need ecologists to use increasingly larger volumes and heterogeneous types of data and approaches designed to harness such data-that is, data-intensive science. In the present article, we argue that data-intensive science will be most successful when used in combination with open science and team science. However, there are cultural barriers to adopting each of these types of science in ecology. We describe the benefits and cultural barriers that exist for each type of science and the powerful synergies realized by practicing team science and open science in conjunction with data-intensive science. Finally, we suggest that each type of science is made up of myriad practices that can be aligned along gradients from low to high level of adoption and advocate for incremental adoption of each type of science to meet the needs of the project and researchers.