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Multi-scale governance and data for sustainable development
Future societal systems will be characterized by heterogeneous human behaviors and data-driven collective action. Complexity will arise as a consequence of the 5th Industrial Revolution and 2nd Data Revolution possible, thanks to a new generation of digital systems and the Metaverse. These technolog...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9753694/ https://www.ncbi.nlm.nih.gov/pubmed/36532845 http://dx.doi.org/10.3389/fdata.2022.1025256 |
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author | Pastor-Escuredo, David Gardeazabal, Andrea Koo, Jawoo Imai, Asuka Treleaven, Philip |
author_facet | Pastor-Escuredo, David Gardeazabal, Andrea Koo, Jawoo Imai, Asuka Treleaven, Philip |
author_sort | Pastor-Escuredo, David |
collection | PubMed |
description | Future societal systems will be characterized by heterogeneous human behaviors and data-driven collective action. Complexity will arise as a consequence of the 5th Industrial Revolution and 2nd Data Revolution possible, thanks to a new generation of digital systems and the Metaverse. These technologies will enable new computational methods to tackle inequality while preserving individual rights and self-development. In this context, we do not only need data innovation and computational science, but also new forms of digital policy and governance. The emerging fragility or robustness of the system will depend on how complexity and governance are developed. Through data, humanity has been able to study a number of multi-scale systems from biological to migratory. Multi-scale governance is the new paradigm that feeds the Data Revolution in a world that would be highly digitalized. In the social dimension, we will encounter meta-populations sharing economy and human values. In the temporal dimension, we still need to make all real-time response, evaluation, and mitigation systems a standard integrated system into policy and governance to build up a resilient digital society. Top-down governance is not sufficient to manage all the complexities and exploit all the data available. Coordinating top-down agencies with bottom-up digital platforms will be the design principle. Digital platforms have to be built on top of data innovation and implement Artificial Intelligence (AI)-driven systems to connect, compute, collaborate, and curate data to implement data-driven policy for sustainable development based on Collective Intelligence. |
format | Online Article Text |
id | pubmed-9753694 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-97536942022-12-16 Multi-scale governance and data for sustainable development Pastor-Escuredo, David Gardeazabal, Andrea Koo, Jawoo Imai, Asuka Treleaven, Philip Front Big Data Big Data Future societal systems will be characterized by heterogeneous human behaviors and data-driven collective action. Complexity will arise as a consequence of the 5th Industrial Revolution and 2nd Data Revolution possible, thanks to a new generation of digital systems and the Metaverse. These technologies will enable new computational methods to tackle inequality while preserving individual rights and self-development. In this context, we do not only need data innovation and computational science, but also new forms of digital policy and governance. The emerging fragility or robustness of the system will depend on how complexity and governance are developed. Through data, humanity has been able to study a number of multi-scale systems from biological to migratory. Multi-scale governance is the new paradigm that feeds the Data Revolution in a world that would be highly digitalized. In the social dimension, we will encounter meta-populations sharing economy and human values. In the temporal dimension, we still need to make all real-time response, evaluation, and mitigation systems a standard integrated system into policy and governance to build up a resilient digital society. Top-down governance is not sufficient to manage all the complexities and exploit all the data available. Coordinating top-down agencies with bottom-up digital platforms will be the design principle. Digital platforms have to be built on top of data innovation and implement Artificial Intelligence (AI)-driven systems to connect, compute, collaborate, and curate data to implement data-driven policy for sustainable development based on Collective Intelligence. Frontiers Media S.A. 2022-12-01 /pmc/articles/PMC9753694/ /pubmed/36532845 http://dx.doi.org/10.3389/fdata.2022.1025256 Text en Copyright © 2022 Pastor-Escuredo, Gardeazabal, Koo, Imai and Treleaven. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Big Data Pastor-Escuredo, David Gardeazabal, Andrea Koo, Jawoo Imai, Asuka Treleaven, Philip Multi-scale governance and data for sustainable development |
title | Multi-scale governance and data for sustainable development |
title_full | Multi-scale governance and data for sustainable development |
title_fullStr | Multi-scale governance and data for sustainable development |
title_full_unstemmed | Multi-scale governance and data for sustainable development |
title_short | Multi-scale governance and data for sustainable development |
title_sort | multi-scale governance and data for sustainable development |
topic | Big Data |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9753694/ https://www.ncbi.nlm.nih.gov/pubmed/36532845 http://dx.doi.org/10.3389/fdata.2022.1025256 |
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