Diversity of thoughtÌýand experience leads to better science. Yet, despite decades of effort, women and racially minoritised groupsÌýremainÌýunderrepresented within many research communities, especially in senior leadership.

Leadership and career development programmes are often offered as a solution within universities and research institutes. While these programmes can be inspirational and impactful, on their own they do notÌýaddressÌýthe deeper, systemic barriers that shape who can access opportunities and progress.ÌýÌý

Why structural change matters: The Gollum EffectÌýÌý

In academia, power is often shared asymmetrically among dominant and minority groups. To address this, we need to focus on the mechanisms that perpetuate these imbalances. Inclusion must go beyond inviting marginalised voices into existing systems, we need to transform how those systems work.Ìý

Recent research on theÌýÌýoffers an interesting metaphor forÌýunderstandingÌýthese dynamics. Like Tolkien’s character obsessively guarding the ring, researchersÌýcan becomeÌýpossessiveÌýover data, ideas, and resources. ThisÌýcreates a hypercompetitiveÌýculture,ÌýlimitsÌýaccess to fundingÌýandÌýopportunities andÌýrestrictsÌýopen science andÌýcollaboration.

Importantly,ÌýthisÌýisÌýnotÌýjustÌýabout individualÌýbehaviour. It reflectsÌýÌýover openness,Ìý disproportionately impacting marginalised groups and early-career researchers and disrupting scientific progress.Ìý

How does this apply in the context ofÌýhealthÌýdataÌýscience?

These dynamics are particularly visible in health data science, where access to data, tools and infrastructure is tightly controlled. So, how can we design systems that enable more equitable participation?

The researchers of the identified potential solutions that support better collaboration and  , several of which focus on infrastructure and data governance, such as:Ìý

  • Establishing clear policies on data ownership and authorship to prevent territorial gatekeeping
  • Mandating trustworthy open data, code sharing, and pre-registration for research projects to encourage and fund multi-institutional and interdisciplinary collaborations
  • Interdisciplinary teamwork and recognising non-traditional research contributions such as technical support and data management

TeamÌýscience

At 51±¬ÁÏÍø, team science is embedded from the outset. This means proactively valuing early career voices, recognising a diversity of skills, and engaging a range of partners across disciplines and sectors. This can be illustrated through the project which aims to drive system change by amplifying the voices of interdisciplinary scientists and technical professionals from diverse backgrounds.Ìý

Team science also underpins theÌýData Curation Skills for Sensitive DataÌýproject, which brings together people across roles and disciplines to build shared standards forÌýhigh qualityÌýdata curation in Trusted Research Environments.ÌýThe projectÌýintentionallyÌýbrings togetherÌýtechnical specialists, governance professionals, operational staff, and researchers, recognising thatÌýexpertiseÌýis distributed and often under-recognised within infrastructure environments.ÌýItsÌýengagement strategyÌýenablesÌýcontributions from individuals in non-academic roles and from institutions of varying scale and resource.ÌýFindings from the project will inform training pathways that are accessible, scalable, and responsive to diverse career trajectories, helping to strengthen workforce inclusion and progression across the sector.Ìý

InclusiveÌýinfrastructureÌý

Developments within health data science offer a unique opportunity to design technical infrastructure thatÌýactively reduces exclusion.ÌýÌýButÌýinclusionÌýdoesn’tÌýhappenÌýby default,ÌýitÌýrequiresÌý.ÌýPrioritising accessibility, usability, and trustworthinessÌýcan help ensure thatÌýtrusted research environmentsÌýareÌýfairÌýand usable in practice, reducing barriers to entry and enabling aÌýbroaderÌýrange of researchers toÌýparticipate.ÌýÌý

OurÌýtechnical infrastructure programmes – including the Health Data ResearchÌý, theÌýÌýService, and theÌýSafe People RegistryÌý– are designed to make datasets easier to discover and support scalable and trustworthy access to sensitive data, supporting more equitable access to health data for research.

Similarly, in collaboration with the UK Health Data Research Alliance,Ìý we have developed the .ÌýThisÌýpractical tool supports trustworthy decision-making and makes data access decisions more transparent and easier to understand for everyone, including researchers, dataÌýcustodiansÌýand theÌýpublic.Ìý

More broadly, buildingÌýtrust in health data science means addressing deeper, systemic sources of mistrustÌýstemmingÌýfrom historical misuseÌýof data,Ìýunethical practices,Ìýmisinformation biased assumptions about minoritised groupsÌýandÌýunequalÌýexperiences within the healthcare system.Ìý

Find out more…

Embedding equity into health data ecosystems – through inclusive infrastructure, equitable policies, and collaborative research cultures – creates the conditions for innovation and better science. You can explore the work mentioned in this blog post further:Ìý Ìý