The Global Passion for Data-ism – Is it An Emergent Tool for Rapid, Adaptive Public Policy? RL Vol. XI No. CCXCIII, MMXVII

The Global Passion for Data-ism –

Is it An Emergent Tool for Rapid, Adaptive Public Policy?

The environment in which public policy is made has entered a period of dramatic change. Widespread use of digital technologies, the Internet and social media means both citizens and governments leave digital traces that can be harvested to generate big data. Policy-making takes place in an increasingly rich data environment, which poses both promises and threats to policy-makers. Helen Margetts, 2013

Public Lecture - RL Vol. XI No. CCXCIII, MMXVII

Costantinos Berhutesfa Costantinos, PhD

Professor of Public Policy & Sustainable Institutional Reforms

https://addisababa.academia.edu/CostyCostantinos

Abstract

In just four decades, the systems of statistics in Africa went through three seismic waves. The first of these occurred immediately in the aftermath of decolonisation. During this time, Africa experienced a decade of dramatic rise in the development of its systems of national statistics, particularly in the implementation of population censuses and household surveys. This lecture focuses on the emerging need for good social and economic data that can help African nations develop statistical systems that will provide on time information on socio-economic development that will affect resource mobilization and allocation more proactively. The research questions addressed the relevance Big Data may have to the huge range of public policy questions. Big data challenges policy makers because it can offer real-time results that require a rapid, adaptive policy in return. Big data is often a rich data, offering refined data points and high quality observations that span different levels of analysis and the data is often fragmented, so researchers spend time trying to locate and access diverse data sets. The data requires translation – between languages, and between disciplines. Data-ism is a recently coined term for a kind of data philosophy or ideology. Big data refers to a process that is used when traditional data mining and handling techniques cannot reveal the insights and meaning of the underlying data. Data that is unstructured or time sensitive or simply very large cannot be processed by relational database engines. The lecture further discusses data modelling, data augmentation, algebraic modelling & algorithm and research initiatives on Big Data and Public Policy. It further elaborates on the promises and threats of big data for public policy-making how big data has changed public policy. Data transformation deals with turning numbers into knowledge, conceptualizing data management: the information value chain mapping the flow of data, matching your needs to the software and triangulation.

Key words: data-ism, big data, algebraic modelling, algorithm data modelling, augmentation & transform

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