Data for science and health: trustworthy data science

Data science is central to the future of health and the scientific endeavour. To support the right tools and people, we are investing £75 million in a five-year programme on data for science and health.

Why it's important 

Data science is transforming how science solves urgent health challenges but progress in this field is inconsistent and is hindered by three systematic blockers:

  • there is a lack of trust in how health data and technologies are built, used and governed,
  • there is little funding for the foundational tools needed for health data science to thrive globally,
  • there are few opportunities to employ the talents of data scientists and research software engineers to solve health challenges.

What we want to achieve 

We have two goals:

  1. Put trust into practice through changing how data and software in health are funded, developed and governed;
  2. Equip and motivate data scientists with tools and opportunities to innovate with health data in the public interest.

Our programme is global, and we want to ensure that people in low- and middle-income countries benefit from innovation with health data, as well as those in high-income countries.

What we’re doing 

In each area below, we’re working to advance the objectives of Wellcome’s new strategy. These include a broad programme of Discovery Research and a focus on the urgent health challenges of mental health, global heating and infectious disease.

Tools to transform

Disproportionate effort is spent in preparing health data for analysis and computational methods now dominate modern science. Despite their importance, little funding is available for the foundational data and software tools used in health data research.

Without the right tools, work with health data is slow, the barrier to entry for data scientists is high, and only well-resourced institutions are able to make substantial progress.

We will fund open source, foundational data and software tools for science and health, with a focus on usability, adoption and long-term sustainability. We will make it easier and more equitable for data scientists globally to innovate with health data. This will build on our completed work:

  • We worked with Hetco Design(opens in a new tab) to map existing open source software used by applied clinical researchers;
  • We commissioned a study of the health data science ecosystem in East Africa;
  • We commissioned a scoping project assessing the technical, institutional and sociological dimensions of trust in data and technology.

Trust in practice

Information about health feels intensely personal and people have concerns about privacy, security and commercial access to health data. Those collecting and using health data must earn the trust of people and society by demonstrating that they are trustworthy.

There are technical, institutional and social aspects to trust, all of which need to work together in practice. These include computational and data security measures, establishing good governance and clear accountability, being transparent about how data is used, and involving people in decisions.

We will:

  • Demonstrate what trustworthy health data science means in practice through our projects and partnerships;
  • Share what we learn openly to influence the field as it develops;
  • The Data for Science and Health priority area hosts Understanding Patient Data(opens in a new tab) (UPD), a team that combines research, policy and advocacy to make the way patient data is used more visible, understandable and trustworthy.

Talent with incentive

Effective health data innovation requires a diverse set of people from multiple disciplines to communicate and work effectively together: data scientists and research software engineers, clinicians and healthcare providers, biomedical researchers, patients and the public, policy and decision-makers. These groups often don’t have a shared understanding of problems and there are few opportunities for them to collaborate effectively.

Our series of Global Health Data Challenges will create multi-disciplinary collaborations aimed at solving some urgent health challenges. This builds on the scoping done by the Open Data Institute. The first data challenge aims to understand effective interventions against anxiety and depression in young people and will be run with Wellcome’s Mental Health priority area.

We will:

  • Strengthen communities of health data innovators internationally;
  • Understand barriers to data science careers in health and tackle them by changing research culture;
  • Encourage and reward non-traditional research outputs and career paths, such as open data sharing and re-usable code.

Active projects and calls for proposals  

Calls for proposals

Landscape analysis – climate, health and digital equity  

The communities that are most vulnerable to the health impacts of climate change tend to be those who are least able to prepare for, adapt to or mitigate against them. Data science and digital tools can be powerful in understanding and preventing the impacts of climate on health, but these approaches need to be equitable to ensure the most vulnerable communities benefit from them.

We're commissioning a landscape analysis of equitable digital approaches that help to explore the impacts of climate on health, such as tools that monitor changes in weather conditions which could affect the spread of infectious diseases. The goal is to capture the current activities and identify the areas that need enhancing.

Next steps 

Read our request for proposals [PDF 199KB].

Send your proposal to Bilal Mateen at The deadline is Friday 2 July 2021, 17:00 BST.  

Selected suppliers will be asked to give an online presentation on Tuesday 27 July 2021. 

Active projects

We are supporting the Lancet and Financial Times Commission(opens in a new tab), Governing health futures 2030: Growing up in a digital world. The Commission is exploring the convergence of digital health, artificial intelligence (AI) and other frontier technologies with universal health coverage (UHC). Read the FT’s Special Report on the Future of AI and Digital Healthcare(opens in a new tab).

Grant funding

The Data for Science and Health programme does not have any funding calls at this time.

Our team 

Data for Science and Health team

  • Becky Knowles, Project Officer
  • Bilal Mateen, Clinical Tech Lead
  • Chantal Wood, Programme Manager
  • Donna James, Programme Officer
  • Dorothea Abok, PA/Team Co-ordinator
  • Ekin Bolukbasi, Global Health Data Challenges Manager
  • Talia Caplan, Graduate Trainee
  • Tariq Khokhar, Head of Data for Science and Health
  • Yo Yehudi, Open Source Tech Lead

Understanding Patient Data team

  • Grace Annan-Callcott, Communications Officer
  • Harri Weeks, Partnerships and Community Manager
  • Iain Millar, Graduate Trainee
  • Natalie Banner, Understanding Patient Data Lead
  • Rebecca Asher & Emily Jesper-Mir, Strategy & Engagement Manager
  • Tom Harrison, Senior Policy Officer

Contact us