Introducing Data for Science and Health at Wellcome
Data science is transforming science and health research. From computational software that accelerates scientific discovery, to models that give us new insights into population health and powerful clinical tools. The future of science and computation are intertwined.
That’s why Wellcome is investing in the data, software and digital tools that makes trustworthy data science possible. Wellcome’s new vision is to support science to solve the urgent health challenges facing everyone — and data science has an important role to play. Wellcome’s Data Blog will continue to show how we use data science internally to make better decisions, and we’ll start to share our work supporting data science more broadly too.
Who are the Data for Science and Health team?
Wellcome’s Data for Science and Health Team exists to make sure trustworthy data science helps solve urgent health challenges like infectious diseases, global heating and mental health. We’re a mix of health data, software and technology experts.
Here’s a flavour of what we’re working on:
Funding technology to make better use of the data available for health research
The Data for Science and Health team are supporting software-based tools and digital infrastructure which have lacked sustainable funding in the past. For example, the team has funded two infectious disease data sharing platforms, IDDO and Vivli , as part of a vision for a FAIR Data Network of Infectious Diseases (FAIR meaning Findable, Accessible, Interoperable, Reusable).
IDDO and Vivli can now enhance their technology, starting with infrastructure to enable the sharing of Covid-19 clinical trials data. They will improve dataset findability, accelerate their data curation capacity, streamline the data access workflow and improve the credit given to data contributors. This will ensure that science can advance in a rapid, robust and innovative way.
Embedding open science principles into our projects
Open science means the outputs and processes of research are available to all. It is crucial for ensuring data scientists can innovate with health data easily and equitably, and it leads to powerful scientific discoveries. That’s why Data for Science and Health are funding teams to develop open source software tools with a particular focus on community, usability, accessibility, adoption, and long-term sustainability.
For example, we are funding OpenSAFELY which is a new approach to analysing NHS electronic health records that has proved instrumental in understanding risk factors for Covid-19 mortality. OpenSAFELY is an exemplar of open science since the team shares all methods and analyses transparently through GitHub, thus showing that their research is a public good which can be used and built on by others. Along with technological aspects, progressing open science also depends upon up-skilling the scientific community for example we have supported the Software Sustainability Institute Collaborations Workshop which provides a space for discussions and learning about research software culture and open source approaches.
Supporting multidisciplinary teams by running global health data challenges
Data challenges are increasingly used to finding solutions to tricky problems. They provide incentives to motivate teams to approach the issue with innovative thinking or methods. Along with a prize for the winning team, these incentives include networking opportunities, mentorship and access to data that typically presents a barrier to answering questions.
Data challenges can be especially powerful for problems that are blocked by siloed research fields, where funding is limited, or where there is a lack of motivation because progress has slowed down. Wellcome’s first data challenge will generate tools and methods to better understand the ‘active ingredients’ in youth anxiety and depression: the factors which make interventions effective. As well as involving young people with lived experience of mental health difficulties, the challenge will encourage applications from multidisciplinary teams that could include clinicians, data scientists, mental health experts and social scientists.
Making the use of patient data in the UK more trustworthy
Data for Science and Health hosts the Understanding Patient Data program, which aims to make the way patient data is used more trustworthy. They work with patient groups, charities, healthcare organisations and policymakers to bring transparency, accountability and public involvement to the way data from health records is used.
The team recently started an engagement project to learn about Black and South Asian people’s views and experiences of health data collection in the UK. Covid-19 has highlighted the health inequalities experienced by Black and South Asian people, and the gaps in health records that make it harder to understand and tackle these problems. These issues can only be properly addressed through engagement and partnership with Black and South Asian people to co-develop solutions — which is what this project aims to do. The team is also working on a number of other research, policy and engagement projects. They’ll write about what they learn on their website or and on twitter.
How can I get involved?
We’ll writing more about what we’re working on in the next few months. Follow this page and keep an eye out on the Wellcome website for upcoming opportunities. Send us an email at ContactDataForScienceAndHealth@wellcome.ac.uk .
