Articles producció científicaEnginyeria Informàtica i Matemàtiques

Give more data

  • Datos identificativos

    Identificador:  imarina:6285443
    Autores:  Nanni, Mirco; Andrienko, Gennady; Barabasi, Albert-Laszlo; Boldrini, Chiara; Bonchi, Francesco; Cattuto, Ciro; Chiaromonte, Francesca; Comande, Giovanni; Conti, Marco; Cote, Mark; Dignum, Frank; Dignum, Virginia; Domingo-Ferrer, Josep; Ferragina, Paolo; Giannotti, Fosca; Guidotti, Riccardo; Helbing, Dirk; Kaski, Kimmo; Kertesz, Janos; Lehmann, Sune; Lepri, Bruno; Lukowicz, Paul; Matwin, Stan; Jimenez, David Megias; Monreale, Anna; Morik, Katharina; Oliver, Nuria; Passarella, Andrea; Passerini, Andrea; Pedreschi, Dino; Pentland, Alex; Pianesi, Fabio; Pratesi, Francesca; Rinzivillo, Salvatore; Ruggieri, Salvatore; Siebes, Arno; Torra, Vicenc; Trasarti, Roberto; van den Hoven, Jeroen; Vespignani, Alessandro
    Resumen:
    © 2020, University of Skovde. All rights reserved. The rapid dynamics of COVID-19 calls for quick and effective tracking of virus transmission chains and early detection of outbreaks, especially in the “phase 2” of the pandemic, when lockdown and other restriction measures are progressively withdrawn, in order to avoid or minimize contagion resurgence. For this purpose, contact-tracing apps are being proposed for large scale adoption by many countries. A centralized approach, where data sensed by the app are all sent to a nation-wide server, raises concerns about citizens’ privacy and needlessly strong digital surveillance, thus alerting us to the need to minimize personal data collection and avoiding location tracking. We advocate the conceptual advantage of a decentralized approach, where both contact and location data are collected exclusively in individual citizens’ “personal data stores”, to be shared separately and selectively (e.g., with a backend system, but possibly also with other citizens), voluntarily, only when the citizen has tested positive for COVID-19, and with a privacy preserving level of granularity. This approach better protects the personal sphere of citizens and affords multiple benefits: It allows for detailed information gathering for infected people in a privacy-preserving fashion; and, in turn this enables both contact tracing, and, the early detection of outbreak hotspots on more finely-granulated geographic scale. The decentralized approach is also scalable to large populations, in that only the data of positive patients need be handled at a central level. Our recommendation is two-fold. First to extend existing decentralized architectures with a light touch, in order to manage the collection of location data locally on the device, and allowthe user to share spatio-temporal aggregates-if and when they want and for specific aims-with health authorities, for instance. Second, we favour a longerterm pursuit of realizing a Personal Data Store vision, giving users the opportunity to contribute to collective good in the measure they want, enhancing self-awareness, and cultivating collective efforts for rebuilding society.
  • Otros:

    Enlace a la fuente original: http://www.tdp.cat/issues16/abs.a389a20.php
    Referencia de l'ítem segons les normes APA: Nanni, Mirco; Andrienko, Gennady; Barabasi, Albert-Laszlo; Boldrini, Chiara; Bonchi, Francesco; Cattuto, Ciro; Chiaromonte, Francesca; Comande, Giovan (2020). Give more data, awareness and control to individual citizens, and they will help COVID-19 containment. Transactions On Data Privacy, 13(1), 61-66
    Referencia al articulo segun fuente origial: Transactions On Data Privacy. 13 (1): 61-66
    Año de publicación de la revista: 2020
    Entidad: Universitat Rovira i Virgili
    Versión del articulo depositado: info:eu-repo/semantics/publishedVersion
    Fecha de alta del registro: 2024-10-12
    Autor/es de la URV: Domingo Ferrer, Josep
    Departamento: Enginyeria Informàtica i Matemàtiques
    URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
    Tipo de publicación: Journal Publications
    ISSN: 2013-1631
    Autor según el artículo: Nanni, Mirco; Andrienko, Gennady; Barabasi, Albert-Laszlo; Boldrini, Chiara; Bonchi, Francesco; Cattuto, Ciro; Chiaromonte, Francesca; Comande, Giovanni; Conti, Marco; Cote, Mark; Dignum, Frank; Dignum, Virginia; Domingo-Ferrer, Josep; Ferragina, Paolo; Giannotti, Fosca; Guidotti, Riccardo; Helbing, Dirk; Kaski, Kimmo; Kertesz, Janos; Lehmann, Sune; Lepri, Bruno; Lukowicz, Paul; Matwin, Stan; Jimenez, David Megias; Monreale, Anna; Morik, Katharina; Oliver, Nuria; Passarella, Andrea; Passerini, Andrea; Pedreschi, Dino; Pentland, Alex; Pianesi, Fabio; Pratesi, Francesca; Rinzivillo, Salvatore; Ruggieri, Salvatore; Siebes, Arno; Torra, Vicenc; Trasarti, Roberto; van den Hoven, Jeroen; Vespignani, Alessandro
    Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
    Áreas temáticas: Ciência da computação, Computer science, theory & methods, Software, Statistics and probability
    Direcció de correo del autor: josep.domingo@urv.cat
  • Palabras clave:

    Contact tracing
    Covid-19
    Mobility data analysis
    Personal data store
    Computer Science
    Theory & Methods
    Software
    Statistics and Probability
    Ciência da computação
    2013-1631
  • Documentos:

  • Cerca a google

    Search to google scholar