Citizen science (CS), that is, the involvement of citizens in data collection or analysis for research projects, is becoming more widespread. This is due to the increasing digitalization of the general public and due to the increasing number of grand challenges that society is facing. Thanks to the contributions of common citizens in data collection and data analysis conducted through technology-mediated interactions, CS can produce a number of benefits for researchers, public organizations, policymakers, citizens, and society as a whole. Given the high density of socio-economic activities in cities, CS can be implemented in a particularly effective way in urban environments to help tackle many “grand challenges”, namely, the pressing environmental and social issues that societies are facing at present. However, CS still has untapped potential to be explored. Indeed, we contend that even though CS involves citizens for precisely defined scientific objectives, the interaction that occurs can also be leveraged to collect data beyond the original aim, thereby producing big data (BD). Through a multiple case studies analysis, we highlight how CS can be used to collect BD as well, which can be a valuable resource for researchers, public organizations, and policymakers. With this aim in mind, this study proposes the definition of a citizen-sourcing framework that jointly employs CS and BD, and it highlights which processes can be implemented to favor the sustainable development of urban environments. Moreover, we also discuss the looming dangers associated with citizen-sourcing as a result of technology-mediated interactions and the use of digital technologies, and we highlight possible future developments.

Citizens and cities: Leveraging citizen science and big data for sustainable urban development

Cappa F.;
2022-01-01

Abstract

Citizen science (CS), that is, the involvement of citizens in data collection or analysis for research projects, is becoming more widespread. This is due to the increasing digitalization of the general public and due to the increasing number of grand challenges that society is facing. Thanks to the contributions of common citizens in data collection and data analysis conducted through technology-mediated interactions, CS can produce a number of benefits for researchers, public organizations, policymakers, citizens, and society as a whole. Given the high density of socio-economic activities in cities, CS can be implemented in a particularly effective way in urban environments to help tackle many “grand challenges”, namely, the pressing environmental and social issues that societies are facing at present. However, CS still has untapped potential to be explored. Indeed, we contend that even though CS involves citizens for precisely defined scientific objectives, the interaction that occurs can also be leveraged to collect data beyond the original aim, thereby producing big data (BD). Through a multiple case studies analysis, we highlight how CS can be used to collect BD as well, which can be a valuable resource for researchers, public organizations, and policymakers. With this aim in mind, this study proposes the definition of a citizen-sourcing framework that jointly employs CS and BD, and it highlights which processes can be implemented to favor the sustainable development of urban environments. Moreover, we also discuss the looming dangers associated with citizen-sourcing as a result of technology-mediated interactions and the use of digital technologies, and we highlight possible future developments.
2022
big data
citizen science
citizen-sourcing
crowd
digitalization
grand challenge
sustainability
urban areas
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12610/64167
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