학술논문

Meaningful Big Data Integration for a Global COVID-19 Strategy
Document Type
Periodical
Source
IEEE Computational Intelligence Magazine IEEE Comput. Intell. Mag. Computational Intelligence Magazine, IEEE. 15(4):51-61 Nov, 2020
Subject
Computing and Processing
Signal Processing and Analysis
Communication, Networking and Broadcast Technologies
COVID-19
Pandemics
Public healthcare
Big Data
Data analysis
Monitoring
Globalization
Language
ISSN
1556-603X
1556-6048
Abstract
With the rapid spread of the COVID-19 pandemic, the novel Meaningful Integration of Data Analytics and Services (MIDAS) platform quickly demonstrates its value, relevance and transferability to this new global crisis. The MIDAS platform enables the connection of a large number of isolated heterogeneous data sources, and combines rich datasets including open and social data, ingesting and preparing these for the application of analytics, monitoring and research tools. These platforms will assist public health author ities in: (i) better understanding the disease and its impact; (ii) monitoring the different aspects of the evolution of the pandemic across a diverse range of groups; (iii) contributing to improved resilience against the impacts of this global crisis; and (iv) enhancing preparedness for future public health emergencies. The model of governance and ethical review, incorporated and defined within MIDAS, also addresses the complex privacy and ethical issues that the developing pandemic has highlighted, allowing oversight and scrutiny of more and richer data sources by users of the system.