Usher Institute

Data-Driven Innovation Hub

The Usher Institute is one of six Data-Driven Innovation Hubs as part of the Edinburgh and South East Scotland City Region Deal.

Through the application of data science, the Usher Institute is driving innovation in health and social care that improves lives. First established in 1902, the Usher Institute is home to the oldest chair of public health in the UK and has a strong international reputation for research and teaching excellence.

Located at Edinburgh BioQuarter, the new Usher building will become a world-leading hub where health and social care research teams collaborate with colleagues from public, private and third sector organisations to deliver data-driven advances in health and social care.

This newly established innovation community will develop solutions to our most pressing sector challenges by integrating the activities of: clinicians, life scientists and data scientists to identify new, co-produced insights; and industry and public sector organisations to extract, apply and commercialise expert knowledge.

The Usher is drawing on Scotland’s mature and world-leading health data assets, establishing ‘DataLoch’ - a unique and secure data service to support transformative research and innovation for the region and beyond. Robust, efficient governance and data-sharing protocols have been developed in partnership with the National Health Service, informed by public perspectives.

An ambitious Talent programme will provide a suite of education and training to support a future workforce with the knowledge and skills to drive the use of data and digital technologies to transform the delivery of care.

Director: Professor Aziz Sheikh

Senior Responsible Officer: Professor Nicholas Mills (Deputy: Professor Ewen Harrison)

Contact: Michael Gray, Implementation Lead:

Data-Driven Innovation Programme

The University of Edinbugh | Data-Driven Innovation | UK Government | Scottish Government | City Region Deal logos

The DDI Programme includes work across ten industry sectors; including Health and Social Care and Public Sector. The delivery hubs will each focus on industry sectors in their area of expertise, coming together to help Edinburgh to become the Data Capital of Europe, creating wider benefits for the economy and society.

The delivery hubs

Bayes Centre

Easter Bush - Agritech

Edinburgh Futures Institute

National Robotarium (in partnership with Heriot-Watt)

Usher Institute

EIDF (Edinburgh International Data Facility)

Find out more on the Data-Driven Innovation Programme website

Health and Social Care Sector

The Usher Institute leads on activity within the DDI Programme focussed on the health and social care sector.  In September 2019 the City Region Deal Joint Committee approved the full Usher Institute business case, which will enable data-driven advances across the sector.

Programmes of work which have approved funding from the DDI programme currently include:


DataLoch logo
A collaboration between the South East Scotland region’s Local Authorities, NHS health boards and The University of Edinburgh that will help generate insights and innovation in health and social care.

Talent programme

Photo of students talking in Potterow
An ambitious plan for education and training will deliver new data capability for the health and social care sector.

Data-Driven Entrepreneurship

Financed by the Scottish Funding Council through DDI (Data-Driven Innovation), the University of Edinburgh is hosting a series of programmes to advance data-driven entrepreneurship and support a recovering society. These activities offer huge opportunities to innovative and entrepreneurial students, academics and staff at the University to develop their ideas, build their skills and connect their ideas to the world. There are also opportunities for external digital start-ups and scale-up companies to join programmes like the Accelerator and benefit from the expertise and talent on offer in Edinburgh.

More information can be found on the Data-Driven Entrepreneurship programme homepage.