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Seismology Perspectives on Integrated, Coordinated, Open, Networked (ICON) Science
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  • Lei Li,
  • Wing Ching Jeremy Wong,
  • Benjamin Schwarz,
  • Tsz Lam Lau
Lei Li
Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring, Central South University, Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring, Central South University

Corresponding Author:[email protected]

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Wing Ching Jeremy Wong
Scripps Institution of Oceanography, University of California San Diego, Scripps Institution of Oceanography, University of California San Diego
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Benjamin Schwarz
GFZ German Research Centre for Geosciences, GFZ German Research Centre for Geosciences
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Tsz Lam Lau
The Chinese University of Hong Kong, The Chinese University of Hong Kong
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Abstract

Seismology focuses on the study of earthquakes and associated phenomena to characterize seismic sources and Earth structure, which both are of immediate relevance to society. This article is composed of two independent views on the state of the ICON principles (Goldman et al., 2021) in seismology and reflects on the opportunities and challenges of adopting them from a different angle. Each perspective focuses on a different topic. Section 1 deals with the integration of multiscale and multidisciplinary observations, focusing on integrated and open approaches, whereas Section 2 discusses computing and open-source algorithms, reflecting coordinated, networked, and open principles. In the past century, seismology has benefited from two co-existing technological advancements - the emergence of new, more capable sensory systems and affordable and distributed computing infrastructure. Integrating multiple observations is a crucial strategy to improve the understanding of earthquake hazards. However, current efforts in making big datasets available and manageable lack coherence, which makes it challenging to implement initiatives that span different communities. Building on ongoing advancements in computing, machine learning algorithms have been revolutionizing the way of seismic data processing and interpretation. A community-driven approach to code management offers open and networked opportunities for young scholars to learn and contribute to a more sustainable approach to seismology. Investing in new sensors, more capable computing infrastructure, and open-source algorithms following the ICON principles will enable new discoveries across the Earth sciences.
Mar 2022Published in Earth and Space Science volume 9 issue 3. 10.1029/2021EA002109