Final published version
Licence: CC BY: Creative Commons Attribution 4.0 International License
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - Tackling the Challenges of 21st-Century Open Science and Beyond
T2 - A Data Science Lab Approach
AU - Hollaway, Michael J.
AU - Dean, Graham
AU - Blair, Gordon
AU - Brown, Mike
AU - Henrys, P.A
AU - Watkins, John
PY - 2020/10/9
Y1 - 2020/10/9
N2 - In recent years, there has been a drive toward more open, cross-disciplinary science taking centre 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, centred 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.
AB - In recent years, there has been a drive toward more open, cross-disciplinary science taking centre 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, centred 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.
U2 - 10.1016/j.patter.2020.100103
DO - 10.1016/j.patter.2020.100103
M3 - Journal article
VL - 1
JO - Patterns
JF - Patterns
SN - 2666-3899
M1 - 100103
ER -