Tectonophysics Perspectives on Integrated, Coordinated, Open, Networked (ICON) Science

EARTH AND SPACE SCIENCE(2022)

引用 0|浏览7
暂无评分
摘要
This article is composed of two independent opinion pieces about the state of integrated, coordinated, open, and networked (ICON) principles (Goldman et al., 2021, https://doi. org/10.1029/2021EO153180; Goldman et al., 2022, https://doi.org/10.1029/2021ea002099) in Tectonophysics and discussion on the opportunities and challenges of adopting them. Each opinion piece focuses on a different topic: (a) global collaboration, technology transfer and application, reproducibility, and data sharing and infrastructure; and (b) field, experimental, remote sensing, and real-time data research and application. Within tectonophysics science, ICON-FAIR principles are starting to be adopted and implemented, however they have not become frequent and there are still plenty of opportunities for further development. During the last decade, standardization reduced fragmentation, facilitated openly available databases, and enabled different modeling methods to be combined. On the other hand, integration and coordination remained insufficient as exemplified by numerous geophysical interpretation programs running on different platforms, lacking the proper documentation and with diverse output formats. We agree that adapting the principles of ICON-FAIR brings high efforts and risks, but in the end, it has great benefits and potential in the tectonophysics community. Plain Language Summary The task of understanding complex geologic events and concepts such as earthquakes, faults, and tectonic plate interactions, requires collecting data from diverse sources; thus making science that is integrated, coordinated, open, and networked (ICON science) is vital to the research, discovery, and forecasting of Earth scientists. Here, we assess the state of ICON principles within the Earth Science sub-field of tectonophysics, and determine where aspects of ICON science are being put into practice at various levels and how we might improve the use of ICON principles in the future.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要