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; Jonathan Wallace; Michaela Black; Raymond 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; Juha Pajula; Adil Umer

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
, Jonathan Wallace
, Michaela Black
, Raymond 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, Juha Pajula, Adil Umer

^*Corresponding author for this work

Jožef Stefan Institute
IIS Biodonostia
Analytics Engines
IBM Ireland Ltd
Ulster University
Public Health England
The Open University
Basque Foundation for Health Innovation and Research (BIOEF)
Katholieke Universiteit Leuven (KU Leuven)
University of Oulu
Dublin City University

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

22 Citations (Scopus)

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.

Original language	English
Article number	9225216
Pages (from-to)	51-61
Journal	IEEE Computational Intelligence Magazine
Volume	15
Issue number	4
DOIs	https://doi.org/10.1109/MCI.2020.3019898
Publication status	Published - 15 Nov 2020
MoE publication type	A1 Journal article-refereed

Funding

Supported by the GYDRA Tool. European Union research fund ‘Big Data Supporting Public Health Policies

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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, J., Black, M., Bond, R., Mulvenna, M., Weston, D., Carlin, P., Bilbao, R., Nikolic, G., Shi, X., De Moor, B., Pikkarainen, M., ... Umer, A. (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 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.",

author = "\{Pita Costa\}, Joao and Marko Grobelnik and Flavio Fuart and Luka Stopar and Gorka Epelde and Scott Fischaber and Piotr Poliwoda and Debbie Rankin and Jonathan Wallace and Michaela Black and Raymond Bond and Maurice Mulvenna and Dale Weston and Paul Carlin and Roberto Bilbao and Gorana Nikolic and Xi Shi and \{De Moor\}, Bart and Minna Pikkarainen and Jarmo P{\"a}{\"a}kk{\"o}nen and Anthony Staines and Regina Connolly and Paul Davis and Juha Pajula and Adil Umer",

note = "Juha Pajula \& Adil Umer are acknowled as authors in the erratum. ",

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Pita Costa, J, Grobelnik, M, Fuart, F, Stopar, L, Epelde, G, Fischaber, S, Poliwoda, P, Rankin, D, Wallace, J, Black, M, Bond, R, 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, Pajula, J & Umer, A 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, Jonathan

AU - Black, Michaela

AU - Bond, Raymond

AU - Mulvenna, Maurice

AU - Weston, Dale

AU - Carlin, Paul

AU - Bilbao, Roberto

AU - Nikolic, Gorana

AU - Shi, Xi

AU - De Moor, Bart

AU - Pikkarainen, Minna

AU - Pääkkönen, Jarmo

AU - Staines, Anthony

AU - Connolly, Regina

AU - Davis, Paul

AU - Pajula, Juha

AU - Umer, Adil

N1 - Juha Pajula & Adil Umer are acknowled as authors in the erratum.

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AB - 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.

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JO - IEEE Computational Intelligence Magazine

JF - IEEE Computational Intelligence Magazine

IS - 4

M1 - 9225216

ER -

Meaningful Big Data Integration for a Global COVID-19 Strategy

Abstract

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Erratum: Meaningful Big Data Integration for a Global COVID-19 Strategy (IEEE Computational Intelligence Magazine DOI: 10.1109/MCI.2020.3019898)

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