Conceptualising value creation in data-driven services: The case of vehicle data

Editorial: Perspectives on the value of Big Data sharing

“…Nowadays, there is a vast corpus of research on Big Data, analytics and how to create and capture value from them (Fosso Wamba et al , 2015; Parvinen et al , 2020; Schüritz et al , 2017; Spiekermann, 2019). Nevertheless, we argue that future research should further question the different facets and dimensions of the value of Big Data and what they have in common with their use in areas such as robotics, autonomous vehicles and the increasing adoption of artificial intelligence (AI) in the public sector (Kaiser et al , 2021; Viscusi et al , 2020) and the challenges of digital transformation for public and private organizations (Lanzolla et al , 2020). This would imply increasing, for example, the capacity of modeling vast amounts of different distributed data (cf.…”

“…Furthermore, the Big Data-related phenomenon of the quantified self (individuals' self-tracking of any kind of biological, physical, behavioral or environmental information: Swan, 2013) has recently been associated with subjects other than human beings, such as cars. Vehicles in general are able to capture sensor data about themselves and about their environment, thus becoming quantified vehicles and creating value to be captured by emerging ecosystems enacted by data-driven services (Kaiser et al , 2021; Stocker et al , 2017). Accordingly, the emergence of different quantified subjects raises questions about the role of Big Data for public safety and security as well as the need for understanding the resulting infrastructural challenges and for designing new platforms and services.…”

DaLiF: a data lifecycle framework for data-driven governments

“…Such big data sources include people, the Internet, smart mobile handset, online social networks (Twitter, Facebook, LinkedIn, Instagram), the Internet of Things (IoT), autonomous vehicle, Global Positioning Systems, smart cities, etc. [28][29][30][31][32][33][34][35]. Globally, there are over 3.5 billion social network users and about 26.66 billion IoT linked devices and sensors [8,32].…”

“…• In the analysis phase, prepare and publish outputs in machine-readable formats [53,55]. • Extraction of value from big data through its extensive use and offers a natural interface with the data users [35,[42][43][44]54].…”

“…The government organizations share data with the rest of the government entities. Data sharing is helpful to achieve greater efficiency in the use and re(use) of data by the government [35,142,152]. It is a key to transparency and economic growth [174].…”