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Responsiveness of open innovation to COVID-19 pandemic: The case of data for good
Due to the COVID-19 pandemic, countries around the world are facing one of the most severe health and economic crises of recent history and human society is called to figure out effective responses. However, as current measures have not produced valuable solutions, a multidisciplinary and open appro...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9041816/ https://www.ncbi.nlm.nih.gov/pubmed/35472151 http://dx.doi.org/10.1371/journal.pone.0267100 |
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author | Scotti, Francesco Pierri, Francesco Bonaccorsi, Giovanni Flori, Andrea |
author_facet | Scotti, Francesco Pierri, Francesco Bonaccorsi, Giovanni Flori, Andrea |
author_sort | Scotti, Francesco |
collection | PubMed |
description | Due to the COVID-19 pandemic, countries around the world are facing one of the most severe health and economic crises of recent history and human society is called to figure out effective responses. However, as current measures have not produced valuable solutions, a multidisciplinary and open approach, enabling collaborations across private and public organizations, is crucial to unleash successful contributions against the disease. Indeed, the COVID-19 represents a Grand Challenge to which joint forces and extension of disciplinary boundaries have been recognized as main imperatives. As a consequence, Open Innovation represents a promising solution to provide a fast recovery. In this paper we present a practical application of this approach, showing how knowledge sharing constitutes one of the main drivers to tackle pressing social needs. To demonstrate this, we propose a case study regarding a data sharing initiative promoted by Facebook, the Data For Good program. We leverage a large-scale dataset provided by Facebook to the research community to offer a representation of the evolution of the Italian mobility during the lockdown. We show that this repository allows to capture different patterns of movements on the territory with increasing levels of detail. We integrate this information with Open Data provided by the Lombardy region to illustrate how data sharing can also provide insights for private businesses and local authorities. Finally, we show how to interpret Data For Good initiatives in light of the Open Innovation Framework and discuss the barriers to adoption faced by public administrations regarding these practices. |
format | Online Article Text |
id | pubmed-9041816 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-90418162022-04-27 Responsiveness of open innovation to COVID-19 pandemic: The case of data for good Scotti, Francesco Pierri, Francesco Bonaccorsi, Giovanni Flori, Andrea PLoS One Research Article Due to the COVID-19 pandemic, countries around the world are facing one of the most severe health and economic crises of recent history and human society is called to figure out effective responses. However, as current measures have not produced valuable solutions, a multidisciplinary and open approach, enabling collaborations across private and public organizations, is crucial to unleash successful contributions against the disease. Indeed, the COVID-19 represents a Grand Challenge to which joint forces and extension of disciplinary boundaries have been recognized as main imperatives. As a consequence, Open Innovation represents a promising solution to provide a fast recovery. In this paper we present a practical application of this approach, showing how knowledge sharing constitutes one of the main drivers to tackle pressing social needs. To demonstrate this, we propose a case study regarding a data sharing initiative promoted by Facebook, the Data For Good program. We leverage a large-scale dataset provided by Facebook to the research community to offer a representation of the evolution of the Italian mobility during the lockdown. We show that this repository allows to capture different patterns of movements on the territory with increasing levels of detail. We integrate this information with Open Data provided by the Lombardy region to illustrate how data sharing can also provide insights for private businesses and local authorities. Finally, we show how to interpret Data For Good initiatives in light of the Open Innovation Framework and discuss the barriers to adoption faced by public administrations regarding these practices. Public Library of Science 2022-04-26 /pmc/articles/PMC9041816/ /pubmed/35472151 http://dx.doi.org/10.1371/journal.pone.0267100 Text en © 2022 Scotti et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Scotti, Francesco Pierri, Francesco Bonaccorsi, Giovanni Flori, Andrea Responsiveness of open innovation to COVID-19 pandemic: The case of data for good |
title | Responsiveness of open innovation to COVID-19 pandemic: The case of data for good |
title_full | Responsiveness of open innovation to COVID-19 pandemic: The case of data for good |
title_fullStr | Responsiveness of open innovation to COVID-19 pandemic: The case of data for good |
title_full_unstemmed | Responsiveness of open innovation to COVID-19 pandemic: The case of data for good |
title_short | Responsiveness of open innovation to COVID-19 pandemic: The case of data for good |
title_sort | responsiveness of open innovation to covid-19 pandemic: the case of data for good |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9041816/ https://www.ncbi.nlm.nih.gov/pubmed/35472151 http://dx.doi.org/10.1371/journal.pone.0267100 |
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