Experience: Data Management for delivering COVID-19 relief in Panama

IF 1.5 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS ACM Journal of Data and Information Quality Pub Date : 2023-09-22 DOI:10.1145/3623511
Luis Del Vasto-Terrientes
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Abstract

A data-driven public sector recognizes data as a key element for implementing policies based on evidence. The open data movement has been a major catalyst for elevating data to a privileged position in many governments around the globe. In Panama, open data has enabled the improvement of data management in each institution. However, it is required to go further to create an integrated data-driven government with a common objective. Public institutions collect a huge amount of data that may never be used, and some others do not contain enough quality to provide trustworthy results. The state of emergency caused by the COVID-19 showed the necessity of establishing a common digital government vision for planning, delivering, and monitoring public services, as well as strengthening the technical foundation in the public sector to improve data value cycle: acquisition, storage, and exploitation. This paper reports from a data custodian perspective how the state of emergency worked as a catalyst to boost government data management, specifically for the Vale Digital program, a social relief linked to the identity card implemented by the Panamanian government during the COVID-19 pandemic, which may possibly be the greatest government data integration to date in terms of impact, data volume, rapid implementation, and institutions involved.
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经验:在巴拿马提供COVID-19救援的数据管理
数据驱动的公共部门认识到数据是实施基于证据的政策的关键要素。开放数据运动一直是将数据提升到全球许多政府特权地位的主要催化剂。在巴拿马,开放数据使每个机构的数据管理得到改善。然而,需要进一步建立一个具有共同目标的综合数据驱动型政府。公共机构收集的大量数据可能永远不会被使用,而其他一些数据的质量不足以提供值得信赖的结果。COVID-19造成的紧急状态表明,有必要建立一个共同的数字政府愿景,以规划、提供和监测公共服务,并加强公共部门的技术基础,以改善数据的价值周期:获取、存储和利用。本文从数据托管的角度报道了紧急状态如何成为促进政府数据管理的催化剂,特别是对valedigital项目,这是巴拿马政府在2019冠状病毒病大流行期间实施的一项与身份证相关的社会救济计划,从影响、数据量、快速实施和涉及的机构来看,这可能是迄今为止最大的政府数据整合。
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来源期刊
ACM Journal of Data and Information Quality
ACM Journal of Data and Information Quality COMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
4.10
自引率
4.80%
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0
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