About: COVID-19 has impacted the global landscape well beyond initial estimates, impacting on both societal and economic fronts. Immediate responses by corporations and governments were geared toward building knowledge so that accurate and efficient programs could be devised toward curbing the impacts of the pandemic on society. However, one aspect to this was noted as to the limited availability of data sharing across platforms, systems, and jurisdictions, leading to limited datasets, hence, rendering inaccurate predictions that can be used to contain and limit the virus outbreak. In view of required immediate actions, volunteered geographic information (VGI) and citizen science concept have emerged, where people voluntarily share location and health status data to circumvent data sharing restrictions imposed upon corporations and governments. This is leading to more accurate predictions and supporting an emergence of alternative tools. This chapter explores this dimension and outlines how people, previously aggressively resisting data sharing, do so willingly in times of emergencies.

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About: COVID-19 has impacted the global landscape well beyond initial estimates, impacting on both societal and economic fronts. Immediate responses by corporations and governments were geared toward building knowledge so that accurate and efficient programs could be devised toward curbing the impacts of the pandemic on society. However, one aspect to this was noted as to the limited availability of data sharing across platforms, systems, and jurisdictions, leading to limited datasets, hence, rendering inaccurate predictions that can be used to contain and limit the virus outbreak. In view of required immediate actions, volunteered geographic information (VGI) and citizen science concept have emerged, where people voluntarily share location and health status data to circumvent data sharing restrictions imposed upon corporations and governments. This is leading to more accurate predictions and supporting an emergence of alternative tools. This chapter explores this dimension and outlines how people, previously aggressively resisting data sharing, do so willingly in times of emergencies. Goto Sponge NotDistinct Permalink

An Entity of Type : fabio:Abstract, within Data Space : covidontheweb.inria.fr associated with source document(s)

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type	abstract
value	COVID-19 has impacted the global landscape well beyond initial estimates, impacting on both societal and economic fronts. Immediate responses by corporations and governments were geared toward building knowledge so that accurate and efficient programs could be devised toward curbing the impacts of the pandemic on society. However, one aspect to this was noted as to the limited availability of data sharing across platforms, systems, and jurisdictions, leading to limited datasets, hence, rendering inaccurate predictions that can be used to contain and limit the virus outbreak. In view of required immediate actions, volunteered geographic information (VGI) and citizen science concept have emerged, where people voluntarily share location and health status data to circumvent data sharing restrictions imposed upon corporations and governments. This is leading to more accurate predictions and supporting an emergence of alternative tools. This chapter explores this dimension and outlines how people, previously aggressively resisting data sharing, do so willingly in times of emergencies.
part of	The Emergence of Voluntary Citizen Networks to Circumvent Urban Health Data Sharing Restrictions During Pandemics
is abstract of	The Emergence of Voluntary Citizen Networks to Circumvent Urban Health Data Sharing Restrictions During Pandemics

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