Original citation:Cordella, Antonio and Tempini, Niccolò (2015) E-government and organizational change: reappraising the role of ICT and bureaucracy in public service delivery.

No abstract

Many organizations develop social media networks with the aim of engaging a wide range of social groups in the production of information that fuels their processes. This effort appears to crucially depend on complex data structures that afford the organization to connect and collect data from myriad local contexts and actors. One such organization, PatientsLikeMe is developing a platform with the aim of connecting patients with one another while collecting self--reported medical data, which it uses for scientific and commercial medical research. Here the question of how technology and the underlying data structures shape the kind of information and medical evidence that can be produced through social media--based arrangements comes powerfully to the fore. In this observational case study I introduce the concepts of information cultivation and social denomination to explicate how the development of such a data collection architecture requires a continuous exercise of balancing between the conflicting demands of patient engagement, necessary for collecting data in scale, and data semantic context, necessary for effective capture of health phenomena in informative and specific data. The study extends the understanding of the 2 context--embeddedness of information phenomena and discusses some of the social consequences of social media models for knowledge making. .

Contemporary digital ecosystems produce vast amounts of data every day. The data are often no more than microscopic log entries generated by the elements of an information infrastructure or system. Although such records may represent a variety of things outside the system, their powers go beyond the capacity to carry semantic content. In this article, we harness critical realism to explain how such data come to matter in specific business operations. We analyse the production of an advertising audience from data tokens extracted from a telecommunications network. The research is based on an intensive case study of a mobile network operator that tries to turn its subscribers into an advertising audience. We identify three mechanisms that shape data-based production and three properties that characterize the underlying pool of data. The findings advance the understanding of many organizational settings that are centred on data processing.

Much of the literature on value creation in social media-based infrastructures has largely neglected the pivotal role of data and their processes. This paper tries to move beyond this limitation and discusses data-based value creation in data-intensive infrastructures, such as social media, by focusing on processes of data generation, use and reuse, and on infrastructure development activities. Building on current debates in value theory, the paper develops a multidimensional value framework to interrogate the data collected in an embedded ethnographical case study of the development of PatientsLikeMe, a social media network for patients. It asks when, and where, value is created from the data, and what kinds of value are created from them, as they move through the data infrastructure; and how infrastructure evolution relates to, and shapes, existing data-based value creation practices. The findings show that infrastructure development can have unpredictable consequences for data-based value creation, shaping shared practices in complex ways and through a web of interdependent situations. The paper argues for an understanding of infrastructural innovation that accounts for the situational interdependencies of data use and reuse. Uniquely positioned, the paper demonstrates the importance of research that looks critically into processes of data use in infrastructures to keep abreast of the social consequences of developments in big data and data analytics aimed at exploiting all kinds of digital traces for multiple purposes.