Data-driven insights in smart cities pilot projects: plenitude and usability of Big Data

Zaitsava, Maryia

;Marku, Elona;Di Guardo, Maria Chiara

2023-01-01

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Abstract

The chapter aims at opening the black box of Big Data (BD) insights creation in the smart cities’ (SM) context. We investigate two macro-dimensions of BD, namely, plenitude ad usability. Plenitude refers to the ability of BD to grow exponentially in size and granularity while usability relates to the ability of BD to be reliable and easy to employ. We jointly examine these macro-dimensions in the context of a large-scale multinational pilot launched in three European cities: Antwerp (Belgium), Helsinki (Finland), and Manchester (United Kingdom). The qualitative approach allowed us to identify four types of data-driven insights: (1) “set up” insights, (2) “evidence base” insights, (3) “data simulation” insights, and (4) “scale up” insights. We found that these scenarios have distinct relevance to a more conscious creation of BD insights in SM pilots. Our study offers a new approach to a better understanding of SM data-driven insights creation. Several implications for policymakers are presented and further discussed.