Till Data Do Us Part: Understanding Data-Based Value Creation in Data-Intensive Infrastructures

Abstract

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.

Values in tension. Clinical quality and civic participation in umbilical cord blood banking in Italy

“…), genomic databases (e.g. Singh ) and biomedical data platforms (Tempini ) that have demonstrated how these infrastructures are sites of multiple processes of valuation and valourisation – including economic, epistemic and social values (e.g. related to identity building and shared sociality).…”

Big data governance of personal health information and challenges to contextual integrity

“…Barrett, Oborn, and Orlikowski (2016) identified six different types of value that different stakeholders gained from interacting on an online health community platform -financial, epistemic, ethical, service, reputational, and platform. However, Tempini (2017) notes data reuse to enhance one stakeholder group's value may make data less valuable to others, because the processes of data generation, use, and reuse, and infrastructure development activities are not easily separated. Moreover, shifting data from one context to another may lessen value for some stakeholders.…”

“…These values are not necessarily contradictory, but data use and reuse is not seamless (Tempini 2017). Dr. Julian Huppert, head of an Independent Review Panel instituted by DMH to provide independent oversight and ensure public accountability for its health endeavors, noted that the NHS PHI data were not as optimized for reuse as DMH had expected: "DeepMind could use AI to help with healthcare, but I think that it found that the state of data in the NHS was not as good as it had hoped so it had to step back from this" (Wakefield 2017, 12).…”

Is the Genie Out of the Bottle? Digital Platforms and the Future of Clinical Trials

“…He collaborated with most of the employees on site, and corroborated the observational and documental material with focused interviews for a total of 30 hours of recording. Some of this ethnographic research has been published as peer-reviewed articles before, but these works did not deal with the issues this article is concerned with (Kallinikos & Tempini, 2014;Tempini, 2015Tempini, , 2017. 8 Scraping is a technical term for the extraction of data from a raw html source, i.e.…”