Tackling the challenges of 21st-century open science and beyond: a data science lab approach

Hollaway, Michael J. ORCID: https://orcid.org/0000-0003-0386-2696; Dean, Graham; Blair, Gordon S. ORCID: https://orcid.org/0000-0001-6212-1906; Brown, Mike; Henrys, Peter A.; Watkins, John ORCID: https://orcid.org/0000-0002-3518-8918. 2020 Tackling the challenges of 21st-century open science and beyond: a data science lab approach. Patterns, 1 (7), 100103. 15, pp. https://doi.org/10.1016/j.patter.2020.100103

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Official URL: http://dx.doi.org/10.1016/j.patter.2020.100103

Abstract/Summary

In recent years, there has been a drive toward more open, cross-disciplinary science taking center stage. This has presented a number of challenges, including providing research platforms for collaborating scientists to explore big data, develop methods, and disseminate their results to stakeholders and decision makers. We present our vision of a “data science lab” as a collaborative space where scientists (from different disciplines), stakeholders, and policy makers can create data-driven solutions to environmental science's grand challenges. We set out a clear and defined research roadmap to serve as a focal point for an international research community progressing toward a more data-driven and transparent approach to environmental data science, centered on data science labs. This includes ongoing case studies of good practice, with the infrastructural and methodological developments required to enable data science labs to support significant increase in our cross- and trans-disciplinary science capabilities.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1016/j.patter.2020.100103
UKCEH and CEH Sections/Science Areas:	Pollution (Science Area 2017-) Soils and Land Use (Science Area 2017-) UKCEH Fellows
ISSN:	2666-3899
Additional Information. Not used in RCUK Gateway to Research.:	Open Access paper - full text available via Official URL link.
Additional Keywords:	DataLabs, data science, virtual, collaborative, transparent, multi-disciplinary, big data
NORA Subject Terms:	Data and Information
Date made live:	05 Oct 2020 15:44 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/528559

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.1016/j.patter.2020.100103

UKCEH and CEH Sections/Science Areas:

Pollution (Science Area 2017-)
Soils and Land Use (Science Area 2017-)
UKCEH Fellows

ISSN:

2666-3899

Additional Information. Not used in RCUK Gateway to Research.:

Open Access paper - full text available via Official URL link.

Additional Keywords:

DataLabs, data science, virtual, collaborative, transparent, multi-disciplinary, big data