Building digital workforce capacity and skills for data-intensive science

Michelle Barker; Bart Dumolyn; Inge van Nieuwerburgh; David Castle; Marcelo Arenas; Konstantinos Repanas; Carlos Casorran; Natalie Denos; Mehdi Gharsallah; Ingvill C. Mochmann; Nobukazu Yoshioka; Seo-Yeung Noh; Karel Luyben; Gard Thomassen; David McAllister; Kevin Ashley; Lauren Clarke; Daniel S. Katz; Todd K. Leen; Tracy Teal; Simon Hodson; Neil Chue Hong

doi:10.1787/e08aa3bb-en

Building digital workforce capacity and skills for data-intensive science

Michelle Barker, Bart Dumolyn, Inge van Nieuwerburgh, David Castle, Marcelo Arenas, Konstantinos Repanas, Carlos Casorran, Natalie Denos, Mehdi Gharsallah, Ingvill C. Mochmann, Nobukazu Yoshioka, Seo-Yeung Noh, Karel Luyben, Gard Thomassen, David McAllister, Kevin Ashley, Lauren Clarke, Daniel S. Katz, Todd K. Leen, Tracy TealSimon Hodson, Neil Chue Hong

Research output: Book/Report › Commissioned report

Abstract / Description of output

This report looks at the human resource requirements for data-intensive science, focusing primarily on research conducted in the public sector, and the related challenges and training needs. Digitalisation is, to some extent, being driven by science, while simultaneously affecting all aspects of scientific practice. Open science, including access to data, is being widely promoted, and investment in cyber-infrastructures and digital platforms is increasing; but inadequate attention has been given to the skills that researchers and research support professionals need to fully exploit these tools. The COVID-19 pandemic, which struck as this report was being finalised, has underscored the critical importance of data-intensive science and the need for strategic approaches to strengthening the digital capacity and skills of the scientific enterprise as a whole. The report includes policy recommendations for various actors and good practice examples to support these recommendations.

Original language	English
Publisher	Organisation for Economic Cooperation and Development (OECD)
Commissioning body	Organisation for Economic Cooperation and Development (OECD)
Number of pages	63
DOIs	https://doi.org/10.1787/e08aa3bb-en
Publication status	Published - 10 Jul 2020

Publication series

Name	OECD Science, Technology and Industry Policy Papers
Publisher	Organisation for Economic Cooperation and Development (OECD)
No.	90
ISSN (Electronic)	2307-4957

Access to Document

10.1787/e08aa3bb-enLicence: Other

The UK Software Sustainability Institute: Phase 3
Chue Hong, N.
EPSRC
1/12/18 → 30/11/23
Project: Research
The Software Sustainability Institute: Phase 2
Chue Hong, N.
EPSRC
1/06/15 → 31/05/19
Project: Research

1 Participation in workshop, seminar, course
1 Membership of public/government advisory/policy group or panel

Cyberinfrastructure Workforce Development Workshop
Neil Chue Hong (Keynote/plenary speaker)
19 Aug 2020
Activity: Participating in or organising an event types › Participation in workshop, seminar, course
Organisation for Economic Cooperation and Development (OECD) (External organisation)
Neil Chue Hong (Advisor)
Sept 2018 → Jul 2020
Activity: Membership types › Membership of public/government advisory/policy group or panel

Cite this

Barker, M., Dumolyn, B., van Nieuwerburgh, I., Castle, D., Arenas, M., Repanas, K., Casorran, C., Denos, N., Gharsallah, M., Mochmann, I. C., Yoshioka, N., Noh, S.-Y., Luyben, K., Thomassen, G., McAllister, D., Ashley, K., Clarke, L., Katz, D. S., Leen, T. K., ... Chue Hong, N. (2020). Building digital workforce capacity and skills for data-intensive science. (OECD Science, Technology and Industry Policy Papers; No. 90). Organisation for Economic Cooperation and Development (OECD). https://doi.org/10.1787/e08aa3bb-en

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title = "Building digital workforce capacity and skills for data-intensive science",

abstract = "This report looks at the human resource requirements for data-intensive science, focusing primarily on research conducted in the public sector, and the related challenges and training needs. Digitalisation is, to some extent, being driven by science, while simultaneously affecting all aspects of scientific practice. Open science, including access to data, is being widely promoted, and investment in cyber-infrastructures and digital platforms is increasing; but inadequate attention has been given to the skills that researchers and research support professionals need to fully exploit these tools. The COVID-19 pandemic, which struck as this report was being finalised, has underscored the critical importance of data-intensive science and the need for strategic approaches to strengthening the digital capacity and skills of the scientific enterprise as a whole. The report includes policy recommendations for various actors and good practice examples to support these recommendations.",

author = "Michelle Barker and Bart Dumolyn and {van Nieuwerburgh}, Inge and David Castle and Marcelo Arenas and Konstantinos Repanas and Carlos Casorran and Natalie Denos and Mehdi Gharsallah and Mochmann, {Ingvill C.} and Nobukazu Yoshioka and Seo-Yeung Noh and Karel Luyben and Gard Thomassen and David McAllister and Kevin Ashley and Lauren Clarke and Katz, {Daniel S.} and Leen, {Todd K.} and Tracy Teal and Simon Hodson and {Chue Hong}, Neil",

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month = jul,

day = "10",

doi = "10.1787/e08aa3bb-en",

language = "English",

series = "OECD Science, Technology and Industry Policy Papers",

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Barker, M, Dumolyn, B, van Nieuwerburgh, I, Castle, D, Arenas, M, Repanas, K, Casorran, C, Denos, N, Gharsallah, M, Mochmann, IC, Yoshioka, N, Noh, S-Y, Luyben, K, Thomassen, G, McAllister, D, Ashley, K, Clarke, L, Katz, DS, Leen, TK, Teal, T, Hodson, S & Chue Hong, N 2020, Building digital workforce capacity and skills for data-intensive science. OECD Science, Technology and Industry Policy Papers, no. 90, Organisation for Economic Cooperation and Development (OECD). https://doi.org/10.1787/e08aa3bb-en

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T1 - Building digital workforce capacity and skills for data-intensive science

AU - Barker, Michelle

AU - Dumolyn, Bart

AU - van Nieuwerburgh, Inge

AU - Castle, David

AU - Arenas, Marcelo

AU - Repanas, Konstantinos

AU - Casorran, Carlos

AU - Denos, Natalie

AU - Gharsallah, Mehdi

AU - Mochmann, Ingvill C.

AU - Yoshioka, Nobukazu

AU - Noh, Seo-Yeung

AU - Luyben, Karel

AU - Thomassen, Gard

AU - McAllister, David

AU - Ashley, Kevin

AU - Clarke, Lauren

AU - Katz, Daniel S.

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AU - Hodson, Simon

AU - Chue Hong, Neil

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AB - This report looks at the human resource requirements for data-intensive science, focusing primarily on research conducted in the public sector, and the related challenges and training needs. Digitalisation is, to some extent, being driven by science, while simultaneously affecting all aspects of scientific practice. Open science, including access to data, is being widely promoted, and investment in cyber-infrastructures and digital platforms is increasing; but inadequate attention has been given to the skills that researchers and research support professionals need to fully exploit these tools. The COVID-19 pandemic, which struck as this report was being finalised, has underscored the critical importance of data-intensive science and the need for strategic approaches to strengthening the digital capacity and skills of the scientific enterprise as a whole. The report includes policy recommendations for various actors and good practice examples to support these recommendations.

U2 - 10.1787/e08aa3bb-en

DO - 10.1787/e08aa3bb-en

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T3 - OECD Science, Technology and Industry Policy Papers

BT - Building digital workforce capacity and skills for data-intensive science

PB - Organisation for Economic Cooperation and Development (OECD)

ER -

Building digital workforce capacity and skills for data-intensive science

Abstract / Description of output

Publication series

Access to Document

Fingerprint

Projects

The UK Software Sustainability Institute: Phase 3

The Software Sustainability Institute: Phase 2

Activities

Cyberinfrastructure Workforce Development Workshop

Organisation for Economic Cooperation and Development (OECD) (External organisation)

Cite this