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2019 Online Information Review
The purpose of this paper is twofold: first, to explore how China uses a social credit system as part of its “data-driven authoritarianism” policy; and second, to investigate how datafication, which is a method to legitimize data collection, and dataveillance, which is continuous surveillance through the use of data, offer the Chinese state a legitimate method of monitoring, surveilling and controlling citizens, businesses and society. Taken together, China’s social credit system is analyzed as an integrated tool for datafication, dataveillance and data-driven authoritarianism.Design/methodology/approachThis study combines the personal narratives of 22 Chinese citizens with policy analyses, online discussions and media reports. The stories were collected using a scenario-based story completion method to understand the participants’ perceptions of the recently introduced social credit system in China.FindingsChina’s new social credit system, which turns both online and offline behaviors into a credit score through smartphone apps, creates a “new normal” way of life for Chinese citizens. This data-driven authoritarianism uses data and technology to enhance citizen surveillance. Interactions between individuals, technologies and information emerge from understanding the system as one that provides social goods, using technologies, and raising concerns of privacy, security and collectivity. An integrated critical perspective that incorporates the concepts of datafication and dataveillance enhances a general understanding of how data-driven authoritarianism develops through the social credit system.Originality/valueThis study builds upon an ongoing debate and an emerging body of literature on datafication, dataveillance and digital sociology while filling empirical gaps in the study of the global South. The Chinese social credit system has growing recognition and importance as both a governing tool and a part of everyday datafication and dataveillance processes. Thus, these phenomena necessitate discussion of its consequences for, and applications by, the Chinese state and businesses, as well as affected individuals’ efforts to adapt to the system.
Currie, Morgan E.; Paris, Britt S.; Donovan, Joan M.
2019 Online Information Review
The purpose of this paper is to expand on emergent data activism literature to draw distinctions between different types of data management practices undertaken by groups of data activists.Design/methodology/approachThe authors offer three case studies that illuminate the data management strategies of these groups. Each group discussed in the case studies is devoted to representing a contentious political issue through data, but their data management practices differ in meaningful ways. The project Making Sense produces their own data on pollution in Kosovo. Fatal Encounters collects “missing data” on police homicides in the USA. The Environmental Data Governance Initiative hopes to keep vulnerable US data on climate change and environmental injustices in the public domain.FindingsIn analysing the three case studies, the authors surface how temporal dimensions, geographic scale and sociotechnical politics influence their differing data management strategies.Originality/valueThe authors build upon extant literature on data management infrastructure, which primarily discusses how these practices manifest in scientific and institutional research settings, to analyse how data management infrastructure is often crucial to social movements that rely on data to surface political issues.
2019 Online Information Review
The purpose of this paper is to examine how claims to “ownership” are asserted over publicly accessible platform data and critically assess the nature and scope of rights to reuse these data.Design/methodology/approachUsing Airbnb as a case study, this paper examines the data ecosystem that arises around publicly accessible platform data. It analyzes current statute and case law in order to understand the state of the law around the scraping of such data.FindingsThis paper demonstrates that there is considerable uncertainty about the practice of data scraping, and that there are risks in allowing the law to evolve in the context of battles between business competitors without a consideration of the broader public interest in data scraping. It argues for a data ecosystem approach that can keep the public dimension issues more squarely within the frame when data scraping is judicially considered.Practical implicationsThe nature of some sharing economy platforms requires that a large subset of their data be publicly accessible. These data can be used to understand how platform companies operate, to assess their compliance with laws and regulations and to evaluate their social and economic impacts. They can also be used in different kinds of data analytics. Such data are therefore sought after by civil society organizations, researchers, entrepreneurs and regulators. This paper considers who has a right to control access to and use of these data, and addresses current uncertainties in how the law will apply to scraping activities, and builds an argument for a consideration of the public interest in data scraping.Originality/valueThe issue of ownership/control over publicly accessible information is of growing importance; this paper offers a framework for approaching these legal questions.
2019 Online Information Review
The purpose of this paper is to review interventions/methods for engaging older adults in meaningful digital public service design by enabling them to engage critically and productively with open data and civic tech.Design/methodology/approachThe paper evaluates data walks as a method for engaging non-tech-savvy citizens in co-design work. These were evaluated along a framework considering how such interventions allow for sharing control (e.g. over design decisions), sharing expertise and enabling change.FindingsWithin a co-creation project, different types of data walks may be conducted, including ideation walks, data co-creation walks or user test walks. These complement each other with respect to how they facilitate the sharing of control and expertise, and enable change for a variety of older citizens.Practical implicationsData walks are a method with a low-threshold, potentially enabling a variety of citizens to engage in co-design activities relating to open government and civic tech.Social implicationsSuch methods address the digital divide and further social participation of non-tech-savvy citizens. They value the resources and expertise of older adults as co-designers and partners, and counter stereotypical ideas about age and ageing.Originality/valueThis pilot study demonstrates how data walks can be incorporated into larger co-creation projects.
2019 Online Information Review
Applied computational ontologies (ACOs) are increasingly used in data science domains to produce semantic enhancement and interoperability among divergent data. The purpose of this paper is to propose and implement a methodology for researching the sociotechnical dimensions of data-driven ontology work, and to show how applied ontologies are communicatively constituted with ethical implications.Design/methodology/approachThe underlying idea is to use a data assemblage approach for studying ACOs and the methods they use to add semantic complexity to digital data. The author uses a mixed methods approach, providing an analysis of the widely used Basic Formal Ontology (BFO) through digital methods and visualizations, and presents historical research alongside unstructured interview data with leading experts in BFO development.FindingsThe author found that ACOs are products of communal deliberation and decision making across institutions. While ACOs are beneficial for facilitating semantic data interoperability, ACOs may produce unintended effects when semantically enhancing data about social entities and relations. ACOs can have potentially negative consequences for data subjects. Further critical work is needed for understanding how ACOs are applied in contexts like the semantic web, digital platforms, and topic domains. ACOs do not merely reflect social reality through data but are active actors in the social shaping of data.Originality/valueThe paper presents a new approach for studying ACOs, the social impact of ACO work, and describes methods that may be used to produce further applied ontology studies.
2019 Online Information Review
Traditional public health methods for tracking contagious diseases are increasingly complemented with digital tools, which use data mining, analytics and crowdsourcing to predict disease outbreaks. In recent years, alongside these public health tools, commercial mobile apps such as Sickweather have also been released. Sickweather collects information from across the web, as well as self-reports from users, so that people can see who is sick in their neighborhood. The purpose of this paper is to examine the privacy and surveillance implications of digital disease tracking tools.Design/methodology/approachThe author performed a content and platform analysis of two apps, Sickweather and HealthMap, by using them for three months, taking regular screenshots and keeping a detailed user journal. This analysis was guided by the walkthrough method and a cultural-historical activity theory framework, taking note of imagery and other content, but also the app functionalities, including characteristics of membership, “rules” and parameters of community mobilization and engagement, monetization and moderation. This allowed me to study HealthMap and Sickweather as modes of governance that allow for (and depend upon) certain actions and particular activity systems.FindingsDraw on concepts of network power, the surveillance assemblage, and Deleuze’s control societies, as well as the data gathered from the content and platform analysis, the author argues that disease tracking apps construct disease threat as omnipresent and urgent, compelling users to submit personal information – including sensitive health data – with little oversight or regulation.Originality/valueDisease tracking mobile apps are growing in popularity yet have received little attention, particularly regarding privacy concerns or the construction of disease risk.
2019 Online Information Review
The purpose of this paper is to present the concept of institutions as compliant environments, using data to monitor and enforce compliance with a range of external policies and initiatives, using the particular example of UK higher education (HE) institutions. The paper differs from previous studies by bringing together a range of policies and uses of data covering different areas of HE and demonstrating how they contribute to the common goal of compliance.Design/methodology/approachThe compliant environment is defined in this context and the author has applied the preliminary model to a range of policies and cases that use and reuse data from staff and students in HE.FindingsThe findings show that the focus on compliance with these policies and initiatives has resulted in a high level of surveillance of staff and students and a lack of resistance towards policies that work against the goals of education and academia.Research limitations/implicationsThis is the first study to bring together the range of areas in which policy compliance and data processing are entwined in HE. The study contributes to the academic literature on data and surveillance and on academic institutions as organisations.Practical implicationsThe paper offers suggestions for resistance to compliance and data processing initiatives in HE.Originality/valueThis is the first study to bring together the range of areas in which policy compliance and data processing are entwined in HE. The study contributes to the academic literature on data and surveillance and on academic institutions as organisations.
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