大数据
透明度(行为)
独创性
数据科学
资产(计算机安全)
代表性启发
公司治理
鉴定(生物学)
欧洲联盟
数据治理
领域(数学)
知识管理
管理科学
计算机科学
定性研究
业务
数据质量
社会学
工程类
营销
服务(商务)
社会心理学
财务
生物
操作系统
植物
经济政策
心理学
数学
计算机安全
纯数学
社会科学
作者
Francesco Mureddu,Juliane Schmeling,Eleni Kanellou
出处
期刊:Transforming Government: People, Process and Policy
[Emerald Publishing Limited]
日期:2020-04-29
卷期号:14 (4): 593-604
被引量:16
标识
DOI:10.1108/tg-08-2019-0082
摘要
Purpose This paper aims to present pertinent research challenges in the field of (big) data-informed policy-making based on the research, undertaken within the course of the European Union-funded project Big Policy Canvas. Technological advancements, especially in the past decade, have revolutionised the way that both every day and complex activities are conducted. It is, thus, expected that a particularly important actor such as the public sector, should constitute a successful disruption paradigm through the adoption of novel approaches and state-of-the-art information and communication technologies. Design The research challenges stem from a need, trend and asset assessment based on qualitative and quantitative research, as well as from the identification of gaps and external framework factors that hinder the rapid and effective uptake of data-driven policy-making approaches. Findings The current paper presents a set of research challenges categorised in six main clusters, namely, public governance framework, privacy, transparency, trust, data acquisition, cleaning and representativeness, data clustering, integration and fusion, modelling and analysis with big data and data visualisation. Originality/value The paper provides a holistic overview of the interdisciplinary research challenges in the field of data-informed policy-making at a glance and shall serve as a foundation for the discussion of future research directions in a broader scientific community. It, furthermore, underlines the necessity to overcome isolated scientific views and treatments because of a high complex multi-layered environment.
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