What is driving the rise in data-driven techniques used by politicians and political campaigns to connect with the concerns and needs of citizens? Will a data-driven approach to political campaign messaging disrupt the "echo chamber" effect that is perceived to emerge within online spaces? Jo Bates finds the role of data science in the development of the democratic process is still far from certain.
AbstractThe article adopts a neo‐Gramscian analytical framework developed in the field of International Political Economy in order to analyze the relationship between an online collective of civil society actors and U.K. government policymakers in the case of the UK's Open Government Data (OGD) initiative. The aim of the article is to consider the neo‐Gramscian notion of trasformismo as a useful conceptual tool for exploring the relations between the OGD advocates and policymakers within the U.K. state. Empirical evidence is presented which suggests that the notion of trasformismo is able to illuminate some of the political processes of absorption, adaptation, and distortion which have emerged during the development of the UK's OGD initiative, and which have functioned to restrict the counterhegemonic potential of OGD in order to shape the initiative toward a distinctly neoliberal framework for action.
The article argues, drawing on interviews, event observations, academic and policy literature, that the UK's Open Government Data (OGD) initiative should be understood as part of a deep seated social and political struggle with significant processes of co-optation and contestation over outcomes underway. The OGD initiative's intersections with both the PSI re-use industry and the UK government's programme of forced 'austerity' and marketisation of public services are problematised. Civil society advocates' vulnerabilities within this context are discussed and a number of recommendations are offered for the progressive shaping of OGD based on egalitarian principles.
This study explores the socio-political shaping of Chinese smart urbanism by examining the power relations between the government (national and municipal), private firms and citizens embedded in smartmentality. Our exploration begins with teasing out key analytical standpoints of Alberto Vanolo's concept of smartmentality applied in neoliberal practices of smart urbanism. Through this analytical framework, we conceptualise Chinafied smartmentality and illustrate how it is actually playing out in China by undertaking documentary research and in-depth interviews from an inductive case study of the Smart Transportation System (STS) in the city of Shijiazhuang. We observe that the idea of Chinafication extends smartmentality with a focus on the power dynamic. We further argue that this Chinafied smartmentality implies uncritical technological solutionism that is state-steered in nature and citizen participation in digital platforms that is performed with limited roles and power of being included. The paper concludes by calling for future research on the critical examination of value co-creation for shaping a truly citizen-centric mode of governance in Chinese smart urbanism.
Purpose: The purpose of this paper was to examine the potential opportunities and risks of sharing agricultural research data in Tanzania identified in the existing research literature.
Design/methodology/approach: The study involved a review of the literature on research data sharing practices.
Findings: The findings indicate that, research data sharing have significant positive benefits among researchers such as increase high research impact; enhancing international community collaboration among researchers with same interests; improving scientific transparency and accuracy of data (Rappert and Bezuidenhout, 2016); increasing research output whereby a single dataset can be used to generate more than one article by different authors; and many more. The risks hampering data sharing practices includes researchers' fears that data will be scooped, poached or misused (Onyancha, 2016); unreliable electric power; lack of fund to support research data sharing activities; absence of institutional governmental support for data management; perceived lack of evidence benefits (Leonelli, Rappert and Bezuidenhout, 2018); and others. However, in Tanzania research data sharing is relatively new, thus, no any governmental agency mandating or encouraging research data sharing; therefore, there is no research data management; no research open data repositories and no research data sharing policy at any agricultural institution in Tanzania. The study recommends that agricultural researchers should be sensitized to share their data, research data policy and data repositories should also be established to support data sharing practices in Tanzania.
Originality and usefulness: From the available literature, this has been the first time that an effort has been made to examine the potential opportunities and risks of sharing agricultural research data in Tanzania. The study could be used by agricultural institutions and other institutions to assess the researchers' needs in supporting research data sharing. Also, it can be used by the government and institutions to see the need of establishing open data repositories and open data policies to support research data sharing.
In line with developments in many areas of business and governance, where bureaucracies of all sorts are increasingly datafied for budgetary reasons and the additional possibilities for automated analysis, the Dutch Police started with so-called Intelligence-Led Policing. This development led to the creation of the Crime Anticipation System (CAS). This data-driven system tries to predict crimes with statistics based on three data sources: BVI (Central Crime Database), GBA (Municipal Administration) and CBS (Demographics from Statistics Netherlands). By analyzing the used data categories with a critical data studies approach, we will show that the epistemological question concerning predictive policing systems turns into an ontological one: how are living environments and police work mutually shaped and determined by data? We will argue that intelligence-driven policing is not only a qualitative shift, but also has its continuities, since already existing ideas and biases concerning suspects and crimes are reproduced in the information and system of CAS.
