Abstract
AbstractCitizen 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.
Highlights
Citizen science (CS), that is, the involvement of citizens in data collection or analysis for research projects, is a phenomenon that dates back to the early 19th century, in recent years it has spread quickly thanks to advancements in information technology (IT) (Sauermann et al, 2020; Young et al, 2019)
By outlining the benefits that can spring from the simultaneous application of CS and big data (BD), we aim to focus the attention of researchers, policymakers, and citizens on this framework and further stimulate consideration of the benefits generated by citizen-sourcing
In this research we provide a number of contributions for theory and practice
Summary
Citizen science (CS), that is, the involvement of citizens in data collection or analysis for research projects, is a phenomenon that dates back to the early 19th century, in recent years it has spread quickly thanks to advancements in information technology (IT) (Sauermann et al, 2020; Young et al, 2019). CS involves common citizens without a specific background requirement in data collection or analysis to advance research projects and improve decision-making processes at the organizational level. Research bodies and public organizations are looking for methods to gather large amounts of data in order to tackle “grand challenges,” that is, the pressing environmental and social issues that we are facing at present (Guida & Carpentieri, 2021; Sauermann et al, 2020) and CS is a promising way to achieve these goals thanks to the involvement of citizen volunteers through technology-mediated interactions (Riesch et al, 2013; Rowbotham et al, 2019). Cities are the places where the majority of social, economic, and environmental issues are concentrated (Acuto et al, 2018; Bai et al, 2018; Hallin et al, 2021)
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