Investment in research, science and innovation

Influencing Change

This is one of a series of notes to support our policy positions as summarised in the RSS Data Manifesto, and was updated in March 2018. To discuss the policies we are advocating, please contact the policy team at policy@rss.org.uk

Summary

'The Government should commit to increased investment in research and innovation to keep pace with other leading scientific nations. This should be accompanied by a 10 year framework for science and innovation.'

Data is not only a crucial aspect of science and research, but is also increasingly a driver of prosperity. The data economy is supported by capability from our research base, and by the links between science, innovation, and industry. Our Data Manifesto supports stronger investment in the UK’s science and research base, and continued growth of UK investment in research and innovation to an internationally competitive level, working toward a target of 3% of GDP.

We see statistics as a vanguard of valid science, which underpins the future performance of science and research. We therefore recommend that training and approaches to research conduct are strengthened so that they cut across disciplinary divides. Commissioners and funders should also seek to strengthen the application and innovation of statistical science, by opening up, as best they can, underlying data and methods, while cautiously dealing with issues such as data sensitivity. Strong collaborative infrastructure should be formed by UK Research and Innovation and the Research Councils, to engage a wider range of businesses, NGOs and public bodies in statistical R&D.

People’s access to opportunities also needs to be addressed. Internationally, global leadership in research is supported by free movement of researchers. To improve the skills pipeline for statistical science and related disciplines and industries, access to education in mathematics, statistics, computation and data science should also be promoted and widened, building pathways of study for the data economy.

Investment in science and research

'The UK needs to grow the funding available for a capable research base to make new discoveries with data, and to increase in real terms our investment in science.'

Between 2007-2013, EU funding to UK science came to approximately £3 billioni and was spread between institutions, individuals and less economically-developed regions (including Cornwall, parts of Wales and Scottish Highlands). [1] A commitment was made in autumn 2016 to underwrite this by adding £4.7 billion to research investment before 2020-2021. We note, however, that the proposed overall change would keep UK investment below the OECD average of 2.4% of GDP. [2] For the UK to remain globally competitive, we support a target of 3% GDP spending on science investment, to put us on par with leading industrialised countries such as the USA and China. To support excellence, the science, research and innovation budget should also be kept to a planned, ten-year framework. A competitive level and timeframe for research funding will help to maintain the UK’s reputation as a destination for students and research professionals to live, work and flourish, and will be crucial in helping the UK secure the international outlook of its higher education, and its research base.

Links between academia and industry could also be better supported: the Dowling Review concluded in 2015 that researchers’ access to industry projects and production of research inspired by industry uses need strong explicit support in the Research Excellence Framework. [3] Additional to this, a stronger collaborative infrastructure should engage a wider range of businesses, NGOs and public bodies in offering their own support for R&D. [4]



i
Net funding - difference between UK-to-EU and EU-to-UK flow of funds

Statistics across our research base

Data and statistical methods form the crucial support or building-blocks to establish findings and new discoveries for our whole research base. However, industry and universities alike report hard-to-fill vacancies in statistics and data analytics, and high and persistent demand for numerical and data-analytical skills.[5] The focus of public funding on research excellence leads, in general, to concentration of resources in leading research institutes, which government Ministers have observed. [6] To establish research findings, impact, and applications for the benefit of the whole research base, all research institutes need to work well with data. We see this as a gap for cross-cutting funding to address.

'Statistics as a discipline is crucial across our whole research base as a foundation for robust scientific discovery and analysis, and for new ‘data science’ applications.'

The UK’s framework for funding should seek appropriately to balance revenue spending (for ongoing research needs such as training) and capital spending (on physical assets such as research equipment). We need to ensure that UK support for people researching and training in areas of the industrial strategy matches up to the message of our investments in new technology and industrial strategy.

To build in more practical support for research across disciplines, Research Councils should put approaches to statistics, information and data at the heart of what they do. Statisticians and mathematicians should be represented more widely on panels and boards to discuss relevant research proposals, and not just within the mathematical sciences. This and other practical approaches to interdisciplinary collaboration should be promoted across all research disciplines, subject to over-arching review across the Research Councils. There is much that can be built upon across the Research Councils. The Engineering and Physical Sciences Research Council (EPSRC) focuses on the development of statistical theory, methodology and innovative applications as part of its mathematical sciences portfolio, and in its reach across disciplines. Other Research Councils including for biological and biomedical sciences, economic and social research, medical research, and the natural environment each also fund statistical research, innovative use of data and methodological development, focusing more on the application of this in the disciplines they support. Individual Research Councils should support better data and better analysis more rather than less, with a shared agenda across Research Councils to strengthen this.

Opening up access to research data

Poor or selective statistical analysis is a primary candidate for what has been termed a reproducibility crisis: the inability to replicate experiments and reproduce experimental results. [7] If analysis is left unchecked, impacts upon the quality of science and research may seriously affect the motivation for funding future research, the value of open research data and the level of public trust. [8] In a survey of 1500 scientists, a “better understanding of statistics” was believed to be the factor which could boost reproducible results the most. [9]

Researchers, although they are widely supportive of open science in principle, struggle over concerns about ownership, responsibility and control. [10] The scale of their scientific work may also affect the desire to share results; smaller, technical, purer studies are perhaps less rewarding for the authors to release.

Interventions are important, on the part of the Research Councils, to plan for and assure the supply of degree-level, doctoral and post-doctoral trainees. For UK Research and Innovation, provision for and monitoring of the supply of skills should also form part of its strategy for valid science and research. Publishers and funders should work together to establish and require key steps for open science.

Endnotes

1. Royal Society. (2016). UK Research and the European Union: the role of the EU in funding UK research. Available at: https://royalsociety.org/~/media/policy/projects/eu-uk-funding/uk-membership-of-eu.pdf

2. Dept. for Business, Energy and Industrial Strategy. (2017). Building our industrial strategy: White Paper. Available at: https://www.gov.uk/government/publications/industrial-strategy-building-a-britain-fit-for-the-future

3. Royal Academy of Engineering (2015) ‘Break down barriers to university-business collaboration to benefit UK economy’ [online], 2 July 2015. http://www.raeng.org.uk/news/news-releases/2015/july/break-down-barriers-to-university-business-collabo#sthash.MmGKihYd.dpuf

4. Wilson, J. pp. 10-11 in Association for British Pharmaceutical Industry (2017) Open for Innovation: UK Biopharma R&D Sourcebook 2016 [PDF]. http://www.abpi.org.uk/media/1358/open_for_innovation_abpi_sourcebook_2016.pdf

5. CBI (2015) ‘Skills emergency could ‘starve growth’’ – CBI/Pearson survey’ [webpage], 10 July 2015. http://www.cbi.org.uk/news/skills-emergency-could-starve-growth-cbi-pearson-survey/
Slide 16 in Fisher, C. ‘LinkedIn Unveils The Top Skills That Can Get You Hired In 2017’ [webpage], LinkedIn Official Blog 20 October 2016. https://blog.linkedin.com/2016/10/20/top-skills-2016-week-of-learning-linkedin

6. Department for Business, Innovation and Skills and Jo Johnson MP (2015) ‘Speech: one nation science’ [webpage] https://www.gov.uk/government/speeches/one-nation-science
Higher Education Statistics Agency (2017) Income and expenditure by HE provider 2015/16 and 2014/15 (Table 1) [XLSX]. https://www.hesa.ac.uk/data-and-analysis/providers/overviews?year=620&topic%5B%5D=606

7. The InterAcademy Partnership for Health. (2016). A call for action to improve reproducibility of biomedical research. Available at: https://acmedsci.ac.uk/file-download/41599-57f7204459be7.pdf

8. Open Science Collaboration. (2015). Estimating the reproducibility of psychological science. Science, 349(6251), p.aac4716. Available at: http://science.sciencemag.org/content/349/6251/aac4716
Nosek, B.A. and Errington, T.M. (2017). Making sense of replications. Elife, 6, p.e23383. Available at: https://elifesciences.org/content/6/e23383

9. Baker. M. (2016). 1,500 scientists lift the lid on reproducibility. Nature News, Nature Publishing Group. Available at: http://www.nature.com/news/1-500-scientists-lift-the-lid-on-reproducibility-1.19970

10. Berghams, S., et al. (2017). Open Data: The Researcher Perspective. Available at: https://www.universiteitleiden.nl/en/research/research-output/social-and-behavioural-sciences/open-data-the-researcher-perspective