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Topics and policy

Open science and data

Overview

Data and digital technologies are transforming the way we live, work and learn. The Royal Society’s Data Programme is developing policy and promoting debate that helps the UK safely and rapidly realise the growing benefits of data science and digital technologies.

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Reports and publications

Read or download all our reports, publications and consultation responses.

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Machine learning

The project aims to increase awareness and demonstrate the potential of machine learning and highlight the opportunities and challenges it presents.

Cybersecurity research

This report recommends new standards, kitemarks and incentives for stronger cybersecurity, supported by changes to research and innovation policy.

Data management and use

The British Academy and the Royal Society are carrying out a project examining new uses of data and their implications, and reviewing the data governance landscape.

Latest from our blog

Our analysis and advice

  • Machine learning: can machines really learn?

    An interactive infographic about machine learning.

    Explore the infographic

  • Machine learning: what do the public think?

    A summary of the findings from a public dialogue exercise on machine learning, carried out during 2016 in conjunction with Ipsos MORI, as a key part of the Royal Society machine learning programme of work.

    Read our summary

  • Data management and use: Governance in the 21st Century

    A review on the needs of a 21st century data governance system by the Royal Society and the British Academy. 

    Read our report

  • Data management and use: Governance in the 21st Century - October 2017 seminar report

    A report from discussions at a British Academy and Royal Society one-year on seminar where experts reviewed priorities for the governance of data management and use.

    Read our report

  • Science as an open enterprise

    The report highlights the need to grapple with the huge deluge of data created by modern technologies.

    Read the report

Also of interest

Fellows working in this area

Professor Dame Wendy Hall

Wendy Hall is a leading computer scientist who has made significant contributions to our understanding of the interactions between humans and large networks of computers, such as the internet. Consequently, Wendy is playing a prominent role in the development of web science as an emerging discipline.

Wendy Hall is a member of the Royal Society and British Academy Data Governance Working Group.  She co-led a review on artificial intelligence for HM Government.

Professor Peter Donnelly

Peter Donnelly is Professor of Statistical Science and Director of the Wellcome Trust Centre for Human Genetics at the University of Oxford. A major focus of Peter’s research work is the development and appli¬cation of sophisticated statistical methods for the analysis of the vast datasets arising in modern genetic studies. Peter is the Chair of the Royal Society’s Machine Learning Working Group. He is CEO and founder of Genomics plc, a company developing and applying advanced analysis and algorithms to large datasets linking genetic variation with human traits and diseases to understand human biology, and improve human health and healthcare.