Meaningful Big Data Integration For a Global COVID-19 Strategy

Joao Pita Costa; Marko Grobelnik; Flavio Fuart; Luka Stopar; Gorka Epelde; Scott Fischaber; Piotr Poliwoda; Debbie Rankin; J. G. Wallace; Michaela Black; RR Bond; Maurice Mulvenna; Dale Weston; Paul Carlin; Roberto Bilbao; Gorana Nikolic; Xi Shi; Bart De Moor; Minna Pikkarainen; Jarmo Pääkkönen; Anthony Staines; Regina Connolly; Paul Davis

doi:10.1109/MCI.2020.3019898

Meaningful Big Data Integration For a Global COVID-19 Strategy

Joao Pita Costa, Marko Grobelnik, Flavio Fuart, Luka Stopar, Gorka Epelde, Scott Fischaber, Piotr Poliwoda, Debbie Rankin, J. G. Wallace, Michaela Black, RR Bond, Maurice Mulvenna, Dale Weston, Paul Carlin, Roberto Bilbao, Gorana Nikolic, Xi Shi, Bart De Moor, Minna Pikkarainen, Jarmo PääkkönenAnthony Staines, Regina Connolly, Paul Davis

Research output: Contribution to journal › Article › peer-review

18 Citations (Scopus)

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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 authorities 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.

Original language	English
Article number	9225216
Pages (from-to)	51-61
Number of pages	11
Journal	IEEE Computational Intelligence Magazine
Volume	15
Issue number	4
Early online date	15 Oct 2020
DOIs	https://doi.org/10.1109/MCI.2020.3019898
Publication status	Published (in print/issue) - 30 Nov 2020

Bibliographical note

Funding Information:
Supported by the GYDRA Tool

Funding Information:
This project was funded by the European Union research fund ‘Big Data Supporting Public Health Policies,’ under GA No. 727721.

Publisher Copyright:
© 2005-2012 IEEE.

Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.

Keywords

COVID-19
Pandemics
Public healthcare
Big Data
Data analysis
Monitoring
Globalization

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/MCI.2020.3019898

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Published_VersionFinal published version, 1.79 MB

Cite this

Pita Costa, J., Grobelnik, M., Fuart, F., Stopar, L., Epelde, G., Fischaber, S., Poliwoda, P., Rankin, D., Wallace, J. G., Black, M., Bond, RR., Mulvenna, M., Weston, D., Carlin, P., Bilbao, R., Nikolic, G., Shi, X., De Moor, B., Pikkarainen, M., ... Davis, P. (2020). Meaningful Big Data Integration For a Global COVID-19 Strategy. IEEE Computational Intelligence Magazine, 15(4), 51-61. Article 9225216. https://doi.org/10.1109/MCI.2020.3019898

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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 authorities 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.",

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note = "Funding Information: Supported by the GYDRA Tool Funding Information: This project was funded by the European Union research fund {\textquoteleft}Big Data Supporting Public Health Policies,{\textquoteright} under GA No. 727721. Publisher Copyright: {\textcopyright} 2005-2012 IEEE. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.",

year = "2020",

month = nov,

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doi = "10.1109/MCI.2020.3019898",

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Pita Costa, J, Grobelnik, M, Fuart, F, Stopar, L, Epelde, G, Fischaber, S, Poliwoda, P, Rankin, D , Wallace, JG , Black, M , Bond, RR , Mulvenna, M, Weston, D, Carlin, P, Bilbao, R, Nikolic, G, Shi, X, De Moor, B, Pikkarainen, M, Pääkkönen, J, Staines, A, Connolly, R & Davis, P 2020, 'Meaningful Big Data Integration For a Global COVID-19 Strategy', IEEE Computational Intelligence Magazine, vol. 15, no. 4, 9225216, pp. 51-61. https://doi.org/10.1109/MCI.2020.3019898

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AU - Grobelnik, Marko

AU - Fuart, Flavio

AU - Stopar, Luka

AU - Epelde, Gorka

AU - Fischaber, Scott

AU - Poliwoda, Piotr

AU - Rankin, Debbie

AU - Wallace, J. G.

AU - Black, Michaela

AU - Bond, RR

AU - Mulvenna, Maurice

AU - Weston, Dale

AU - Carlin, Paul

AU - Bilbao, Roberto

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AU - De Moor, Bart

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AU - Staines, Anthony

AU - Connolly, Regina

AU - Davis, Paul

N1 - Funding Information: Supported by the GYDRA Tool Funding Information: This project was funded by the European Union research fund ‘Big Data Supporting Public Health Policies,’ under GA No. 727721. Publisher Copyright: © 2005-2012 IEEE. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.

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N2 - 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 authorities 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.

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KW - Pandemics

KW - Public healthcare

KW - Big Data

KW - Data analysis

KW - Monitoring

KW - Globalization

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DO - 10.1109/MCI.2020.3019898

M3 - Article

SN - 1556-603X

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SP - 51

EP - 61

JO - IEEE Computational Intelligence Magazine

JF - IEEE Computational Intelligence Magazine

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M1 - 9225216

ER -

Meaningful Big Data Integration For a Global COVID-19 Strategy

Abstract

Bibliographical note

Keywords

UN SDGs

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