Heliophysics and space weather information architecture and innovative solutions: ways forward
Over the past 10 years, a paradigm shift has happened in the world of science and information technology. Open science is becoming the de facto standard, as underlined by the recent recommendation on Open Science approved by the United Nations Educational, Scientific and Cultural Organization (UNESC...
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Veröffentlicht in: | Advances In Space Research 2024-05 |
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Sprache: | eng |
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Zusammenfassung: | Over the past 10 years, a paradigm shift has happened in the world of science and
information technology. Open science is becoming the de facto standard, as
underlined by the recent recommendation on Open Science approved by the United
Nations Educational, Scientific and Cultural Organization (UNESCO) in November
2021. In parallel, artificial intelligence (AI) and machine learning (ML) technologies are
already part of our daily life, profoundly impacting our societies. This reality is far
different from when the 2015-2025 COmmittee on SPAce Research
(COSPAR)/International Living With a Star (ILWS) Space weather roadmap was laid
down by Schrijver et al. (2015).
Hence, when the COSPAR International Space Weather Action Teams (ISWAT)
initiated community-wide efforts, back in 2018, to join forces in order to advance space
weather predictive capabilities, four ISWAT overarching activities were eventually
established: assessment, information architecture and data utilization, innovative
solutions and education/outreach. These topics are indeed transversal activities across
all subfields of space weather research, focusing on either the variability of
heliospheric regions or physical phenomena and their specific space weather
impacts.
Here, we present the combined output of the information architecture and innovative
solutions working groups. The first part is related to the heliophysics and space
weather information architecture key building blocks (section 2). The second part is
dedicated to open science tools and infrastructures, first detailing the tools to boost
open science (section 3), then presenting actual and upcoming open science
infrastructures (section 4). The third part is related to AI/ML solutions applied to the
data available through this information architecture (section 5). The last part tries to
encompass the breadth of activity presented and provides a number of
recommendations, underlining some opportunities but also challenges ahead. Overall,
this paper tries to highlight how powerful this open science ecosystem is, but also
fragile, requiring sustained support from its various decision makers internationally. |
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ISSN: | 0273-1177 |