| dc.creator | Pastor-Escuredo, D. | |
| dc.creator | Gardeazabal Monsalue, A. | |
| dc.creator | Koo, J. | |
| dc.creator | Imai, A. | |
| dc.creator | Treleaven, P. | |
| dc.date | 2023-01-30T21:24:49Z | |
| dc.date | 2023-01-30T21:24:49Z | |
| dc.date | 2022 | |
| dc.date.accessioned | 2023-07-17T20:10:17Z | |
| dc.date.available | 2023-07-17T20:10:17Z | |
| dc.identifier | https://hdl.handle.net/10883/22479 | |
| dc.identifier | 10.3389/fdata.2022.1025256 | |
| dc.identifier.uri | https://repositorioslatinoamericanos.uchile.cl/handle/2250/7514223 | |
| dc.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. | |
| dc.language | English | |
| dc.publisher | Frontiers Media S.A. | |
| dc.rights | CIMMYT manages Intellectual Assets as International Public Goods. The user is free to download, print, store and share this work. In case you want to translate or create any other derivative work and share or distribute such translation/derivative work, please contact CIMMYT-Knowledge-Center@cgiar.org indicating the work you want to use and the kind of use you intend; CIMMYT will contact you with the suitable license for that purpose | |
| dc.rights | Open Access | |
| dc.source | 5 | |
| dc.source | 2624-909X | |
| dc.source | Frontiers in Big Data | |
| dc.source | 1025256 | |
| dc.subject | AGRICULTURAL SCIENCES AND BIOTECHNOLOGY | |
| dc.subject | Multi-Scale Systems | |
| dc.subject | Collective Intelligence | |
| dc.subject | Federated Learning | |
| dc.subject | ARTIFICIAL INTELLIGENCE | |
| dc.subject | GOVERNANCE | |
| dc.subject | NETWORKS | |
| dc.subject | RESILIENCE | |
| dc.subject | Sustainable Agrifood Systems | |
| dc.title | Multi-scale governance and data for sustainable development | |
| dc.type | Article | |
| dc.type | Published Version | |
| dc.coverage | Switzerland | |
