Contents
Open Research across Disciplines
How the principles of open research can be applied to your disciplineHealth Sciences and Medicine
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Case Studies
UKRN case study: Health sciences; biomedical research, specialising in endocrinology and metabolism
University of Surrey case study: Using virtual representations in mHealth application interventions for health-related behaviour change
University of Surrey case study: OCTAVA: An open-source toolbox for harmonised analysis of clinical angiography images to support discovery of novel biomarkers
University of Surrey case study: Maximising the impact of patient-doctor video observation data
University of Surrey case study: Creating an internationally registered and fully accessible search strategy code for systematic reviews
University of Bristol case study: Generating research impact during a pandemic: Timing matters.
University of Bristol case study: Open research practices in epidemiology.
University of Bristol case study: Bridging Gaps: Improving access to primary care with women who experience severe and multiple disadvantage. Video.
University of Bristol case study: ALSPAC’s use of data notes to promote teamwork and discoverability. Video.
University of Sheffield case study: Ian Sudbery on Identifying gene regulatory sequences in multiple myeloma. Video
University of Suffolk case study: How My Research and Practices Support University of Suffolk Open Access and Open Science Agenda
Examples of open research practices
Open Methods: The “Unseating Big Pharma” case study involves collaboration from 15 countries with the aim to end the legacy of big pharma. Scientists are working together in an effort to show how an open-science model can end dependency on manufacturers and benefit vaccine equity. (Unseating big pharma: the radical plan for vaccine equity (nature.com))
Open Data: “Carsten Brink works with sensitive personal data in the field of radiotherapy for cancer patients. Having FAIR (Findable, Accessible, Interoperable, Reusable) data is essential to the researchers in his field, because they need interoperable data from a large number of patients to predict outcomes. The researchers in his field used to gather data from many different institutes and pool them in one physical location to run models. But, because they need to preserve the patients’ confidentiality, physically moving the data is a legally complicated task. Instead, they now work with distributed learning, which allows them to analyse data at other institutes without having to physically move them.”
Resources
General Resources
- Kostkova, P., Brewer, H., de Lusignan, S., Fottrell, E., Goldacre, B., Hart, G., … and Ross, E. (2016). Who owns the data? Open Data for healthcare. Frontiers in public health, 4. https://www.frontiersin.org/articles/10.3389/fpubh.2016.00007/full
- Guides for MRC funded studies. https://mrc.ukri.org/research/policies-and-guidance-for-researchers/open-research-data-clinical-trials-and-public-health-interventions/
- https://mrc.ukri.org/research/policies-and-guidance-for-researchers/open-access-policy/
- Guide for DHSC and NIHR funded studies. https://www.nihr.ac.uk/documents/nihr-open-access-policy/12251
- Allen C, Mehler, D.M.A. (2019) Open science challenges, benefits and tips in early career and beyond. PLoS Biol 17(5): e3000246. https://doi.org/10.1371/journal.pbio.3000246
- Case studies: working with transcript data; working with sensitive survey data. https://howtofair.dk/how-to-fair/#humanities
- STEM Podcast about Open Pharma. Open Pharma – driving positive change in the communication of pharma-sponsored research: Dr Joana Osório (buzzsprout.com)
- Kwasnicka, D., Keller, J., Perski, O., Potthoff, S., ten Hoor, G., & Ainsworth, B. et al. (2022). White Paper: Open Digital Health – accelerating transparent and scalable health promotion and treatment. Health Psychology Review, 1-17. https://doi.org/10.1080/17437199.2022.2046482
- Héroux ME, Butler AA, Cashin AG, et al Quality Output Checklist and Content Assessment (QuOCCA): a new tool for assessing research quality and reproducibility BMJ Open 2022;12:e060976. doi: 10.1136/bmjopen-2022-060976.
https://bmjopen.bmj.com/content/12/9/e060976 - Harris JK, Combs TB, Johnson KJ, Carothers BJ, Luke DA, Wang X. Three Changes Public Health Scientists Can Make to Help Build a Culture of Reproducible Research. Public Health Reports. 2019;134(2):109-111. doi:10.1177/0033354918821076.
https://journals.sagepub.com/doi/10.1177/0033354918821076
Open Methods
- Best Practice for Mental Health Data Science: Checklist. https://mhdss.ac.uk/best-practice-mental-health-data-science
- Best Practice for Mental Health Data Science: case studies. https://mhdss.ac.uk/case-studies
- UKRN primer, pre-registration and registered reports. https://www.ukrn.org/primers/
- PROSPERO: Registration for systematic reviews with a health-related outcome. https://www.crd.york.ac.uk/PROSPERO/#aboutpage
- Protocols: An online platform for developing and sharing reproducible methods. https://www.protocols.io
- University of Sheffield discipline-specific guidance on how to make research data and software FAIR (findable, accessible, interoperable & reusable). This pilot was conducted in seven departments across the University: Architecture, Biosciences, English, Geography, Mechanical Engineering, Psychology, and the School of Health and Related Research. You can find the full set of checklists from the pilot departments at: https://doi.org/10.15131/shef.data.20496855.v2
Open Data
- Open access dataset. https://data.england.nhs.uk/dataset
- Link for list of dataset archives. https://library.bath.ac.uk/research-data/finding-data/health-medicine
- Collection of physiological data and software. https://fairsharing.org/biodbcore-000488/
Open Outputs
- Preprint repositories.
- Medicine and Health sciences preprint repository. https://www.medrxiv.org/
- Open Access Journals
This page is adapted and extended from: Farran, E. K., Silverstein, P., Ameen, A. A., Misheva, I., & Gilmore, C. (2020, December 15). Open Research: Examples of good practice, and resources across disciplines. https://doi.org/10.31219/osf.io/3r8hb