Data-Intensive Ecological Research Is Catalyzed by Open Science and Team Science

被引:41
|
作者
Cheruvelil, Kendra Spence [1 ,2 ]
Soranno, Patricia A. [2 ]
机构
[1] Michigan State Univ, Lyman Briggs Coll, E Lansing, MI 48824 USA
[2] Michigan State Univ, Dept Fisheries & Wildlife, E Lansing, MI 48824 USA
基金
美国食品与农业研究所;
关键词
data-intensive science; open science; team science; ecology; science culture; gradient of adoption; BIG-DATA; MACROSYSTEMS ECOLOGY; CHALLENGES; COLLABORATION; DIVERSITY; EVOLUTION; NETWORK; ETHICS; FUTURE; MODEL;
D O I
10.1093/biosci/biy097
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
引用
收藏
页码:813 / 822
页数:10
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