Methods for reproducible shipboard SFA nutrient measurement using RMNS and automated data processing

Debates on the temporal shift associated with digitalization often stress notions of speed and acceleration. With the advent of big data and predictive analytics, the time-compressing features of digitalization are compounded within a distinct operative logic: that of pre-emption. The temporality of pre-emption attempts to project the past into a simulated future that can be acted upon in the present; a temporality of pure imminence. Yet, inherently paradoxical, pre-emption is marked by myriads of contrasts and frictions as it is caught between the supposedly all-encompassing knowledge of the data-processing ‘Machine’, and the daily reality of decision-making practices by relevant social actors. In this article, we explore the contrasting temporalities of automated data processing and predictive analytics, using policing as an illustrative example. Drawing on insights from two cases of predictive policing systems that have been implemented among UK police forces, we highlight the prevalence of counter-temporalities as predictive analytics is situated in institutional contexts and consider the conditions of possibility for agency and deliberation. Analysing these temporal tensions in relation to ‘slowness’ as a mode of resistance, the contextual examination of predictive policing advanced in the article provides a contribution to the formation of a deeper awareness of the politics of time in automated data processing; one that may serve to counter the imperative of pre-emption that, taken to the limit, seeks to foreclose the time for politics, action and life.

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Pharmacy Automated Data Processing System by Mail

American Journal of Health-System Pharmacy ◽

10.1093/ajhp/24.1.22 ◽

1967 ◽

Vol 24 (1) ◽

pp. 22-25

Author(s):

Cecil L. Waggoner

Keyword(s):

Data Processing ◽

Processing System ◽

Data Processing System ◽

Automated Data Processing

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Procurement Strategy For Automated Data Processing Equipment

Journal of Purchasing ◽

10.1111/j.1745-493x.1970.tb00145.x ◽

1970 ◽

Vol 6 (2) ◽

pp. 48-59 ◽

Cited By ~ 1

Author(s):

James A. Chamblee

Keyword(s):

Data Processing ◽

Processing Equipment ◽

Automated Data Processing ◽

Procurement Strategy

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Data Protection Impact Assessments as rule of law governance mechanisms

Data & Policy ◽

10.1017/dap.2020.3 ◽

2020 ◽

Vol 2 ◽

Author(s):

Swee Leng Harris

Keyword(s):

Human Rights ◽

Comparative Analysis ◽

Data Processing ◽

Case Studies ◽

Rule Of Law ◽

Data Protection ◽

Environmental Law ◽

Administrative Law ◽

Automated Data Processing ◽

Just Society

Abstract Rule of law principles are essential for a fair and just society and apply to government activities regardless of whether those activities are undertaken by a human or automated data processing. This article explores how Data Protection Impact Assessments (DPIAs) could provide a mechanism for improved rule of law governance of data processing systems developed and used by government for public purposes in civil and administrative areas. Applying rule of law principles to two case studies provides a sketch of the issues and concerns that this article’s proposals for DPIAs seek to address. The article undertakes comparative analysis to find relevant principles and concepts for governance of data processing systems, looking at human rights impact assessments, administrative law, and process rights in environmental law. Drawing on this comparative analysis to identify specific recommendations for DPIAs, the article offers guidance on how DPIAs could be used to strengthen the governance of data processing by government in rule of law terms.

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