Skills Policy Awards 2023/2024

Process and Delivery  

Successful proposals were paired with mentors for 1:1 input and are supported by The Skills Team to develop their connections among national skills stakeholders and supported to co-produce policy outputs and briefings.  

This structured mentorship approach and Turing’s supportive role affords additional opportunities to work alongside colleagues in research, government and/or industry environments and turn valuable research into policy.  

The review process consisted of internal eligibility checks, an academic review panel and a tension meeting with a panel consisting of senior Turing staff from the Skills Team and AI Programme, and representatives from government and the third sector.  

Skills Policy Projects: 

• Dr Emma Karoune, The Turing Way: This project aims to address the gap in the policy landscape that would standardise and strengthen specialised research infrastructure roles alongside the traditional roles in data science. The aim is to professionalise dedicated specialised as well as general data science roles for ensuring high-quality ethical research at institutional and national levels. To do this, their goals are to curate and centralise definitions and skill lists for traditional and infrastructure data science roles in collaboration with stakeholders from national and international institutions for use in policy, hiring and career development.  

• Dr Panos Panagiotopoulos, Queen Mary University of London: The AI Council Roadmap identifies the need to remove barriers that will enable organisations to make better use of data skills and streamline investments in data-driven transformation. This project focuses on the nature and development of data capabilities in organisations, their practical assessment and policy implications for organisational support. The project will build on the resources of the Data Skills Portal with one of its primary objectives being the validation and redevelopment of the self-assessment tool in different organisational contexts. The outcomes of this work will significantly boost the depth and number of case studies that the Taskforce can showcase. The project has further implications for the professionalisation of data science as embedded in organisational capabilities.  

• Dr Eilis Hannon, University of Exeter: Data science is no longer the preserve of mathematicians and computer scientists. Educational activities are appearing across the full spectrum of degree programmes, from the sciences, through business to humanities. This integration of data science training across all education sectors is essential to ensure we can meet the significant demand in the UK economy for data literacy. This project aims to collate and share the successes and challenges of delivering data science education across a range of disciplines and environments. The primary output will be a manifesto of the best pedagogic approaches for data science education that reflects the diversity of education environment and student background.  

• Yo Yehudi, Open Life Sciences: Open Life Science (OLS) is an organisation dedicated to growing open science ambassadors who create open equitable communities in their own scientific and local domains. This work addresses a gap in the policy landscape that operationalises the values exemplified by OLS – centering EDIA principles of widening participation in higher education and data science and strengthening organisations’ infrastructure to provide diversified career and funding opportunities. This project enables OLS to engage with the policy ecosystem – proposing open science projects on policy interventions, transferring knowledge from data science communities to inform policies, and upskilling the next generation of a diverse workforce in effectively engaging with policymakers. 

If you’re interested in learning more about the awards and national skills work at the Turing, get in touch at [email protected].