References
- 1Abele-Brehm, AE, et al. 2019. Attitudes toward open science and public data sharing. Social Psychology, 50(4): 252–260. DOI: 10.1027/1864-9335/a000384
- 2Adams, J. 2022b.
FAIR video case studies . The University of Sheffield. Collection. DOI: 10.15131/shef.data.c.6165894 - 3Adams, J, et al. 2022a.
Departmental FAIR checklists . The University of Sheffield. Workflow. DOI: 10.15131/shef.data.20496855 - 4Calamai, S and Frontini, F. 2018. FAIR data principles and their application to speech and oral archives. Journal of new music research, 47(4): 339–354. DOI: 10.1080/09298215.2018.1473449
- 5Chue Hong, N, et al. 2022. FAIR principles for research (FAIR4RS Principles v1.0). Research Data Alliance. DOI: 10.15497/RDA00068
- 6Fecher, B, Friesike, S and Hebing, M. 2015. What drives academic data sharing? PloS one, 10(2):
e0118053–e0118053 . DOI: 10.1371/journal.pone.0118053 - 7H2020 Programme. 2016. H2020 Programme Guidelines on FAIR Data Management in Horizon 2020 (Version 3.0). European Commission. Directorate-General for Research & Innovation.
- 8Huang, X, et al. 2012. Willing or unwilling to share primary biodiversity data: Results and implications of an international survey. Conservation letters, 5(5): 399–406. DOI: 10.1111/j.1755-263X.2012.00259.x
- 9Library Carpentry. 2019. Top 10 FAIR data and software things. Available at
https://librarycarpentry.org/Top-10-FAIR/ [last accessed 24 November 2022]. - 10McKiernan, EC, et al. 2016. Point of view: How open science helps researchers succeed. eLife, 5:
e16800 . DOI: 10.7554/eLife.16800 - 11Munafò, M, et al. 2017. A manifesto for reproducible science. Nature Human Behaviour, 1(1): 0021–0021. DOI: 10.1038/s41562-016-0021
- 12Norris, E and O’Connor, DB. 2019. Science as behaviour: Using a behaviour change approach to increase uptake of open science. Psychology & Health, 34(12): 1397–1406. DOI: 10.1080/08870446.2019.1679373
- 13Perrier, L, Blondal, E and MacDonald, H. 2020. The views, perspectives, and experiences of academic researchers with data sharing and reuse: A meta-synthesis. PloS one, 15(2):
e0229182–e0229182 . DOI: 10.1371/journal.pone.0229182 - 14Pierce, HH, et al. 2019. Credit data generators for data reuse. Nature, 570(7759): 30–32. DOI: 10.1038/d41586-019-01715-4
- 15Stewart, AJ, et al. 2021. Improving research quality: the view from the UK Reproducibility Network institutional leads for research improvement. BMC research notes, 14(1): 458–458. DOI: 10.1186/s13104-021-05883-3
- 16Suber, P. 2016.
Promoting Open Access in the Humanities . In Knowledge unbound: Selected writings on open access, 2002–2011. London, England: The MIT Press. pp. 331–340. DOI: 10.7551/mitpress/8479.003.0045 - 17Tenopir, C, et al. 2011. Data sharing by scientists: Practices and perceptions. PloS one, 6(6):
e21101–e21101 . DOI: 10.1371/journal.pone.0021101 - 18UKRN. 2022. Open research across disciplines: How the principles of open research can be applied to your discipline. Available at
https://www.ukrn.org/disciplines/ [last accessed 23 November 2022]. - 19University of Sheffield. 2021. University of Sheffield Research Strategy Delivery Plan (internal document).
- 20University of Sheffield. n.d. Research software engineering (RSE). Available at
https://www.sheffield.ac.uk/dcs/research/research-software-engineering [last accessed 23 November 2022]. - 21Wilkinson, MD, et al. 2016. The FAIR guiding principles for scientific data management and stewardship. Scientific Data, 3:
160018 . DOI: 10.1038/sdata.2016.18 - 22Wingham, J and Tipuric, M. 2022.
‘202207_MEC Fair checklist’ . In Adams, J, et al. (eds.), 2022a Departmental FAIR checklists. The University of Sheffield. Workflow. DOI: 10.15131/shef.data.20496855 - 23Zagrodzka, Z and Simsek, D. 2022.
‘202207_Biosciences Fair checklist’ . In Adams, J, et al. (eds.), 2022a Departmental FAIR checklists. The University of Sheffield. Workflow. DOI: 10.15131/shef.data.20496855 - 24Zhu, Y. 2020. Open-access policy and data-sharing practice in UK academia. Journal of Information Science, 46(1): 41–52. DOI: 10.1177/0165551518823174
