The Functions and Purpose of Science Indicators in Guiding Research and Policy

Every year, governments and institutions spend enormous sums on research. But how do they know if that money is well spent? How does a country decide whether to fund artificial intelligence over agricultural biotechnology, or measure whether its universities are keeping pace with the rest of the world? The answer lies in science indicators: the quantitative measures that turn the messy, sprawling activity of scientific research into data that can be tracked, compared, and acted upon. For anyone studying informetrics and scientometrics, understanding what these indicators actually do is the key to understanding how modern science is governed.

What science indicators are meant to do 🔗

Science indicators are statistical measures that describe the state of a science and technology system. They capture things like research expenditure, the number of researchers, patents filed, and scientific publications produced. But it is important to understand that an indicator is more than just a raw number. According to the U.S. National Research Council, indicators are distinct from raw data and basic statistics; they are constructed measures designed to stand in for something larger and harder to observe directly.

This distinction matters. Many of the things we genuinely care about, such as a nation’s scientific ingenuity or the long-term value of basic research, cannot be measured directly. So analysts use proximate measures that can be observed, such as the number of PhDs awarded in a given period, as a signal of the underlying capacity. The OECD describes how science, technology and innovation indicators describe a system’s strengths, weaknesses and unique features so that countries can act on them.

From statistics to indicators 🔗

A single statistic, such as total R&D spending, tells you very little on its own. It becomes an indicator when it is placed in a meaningful context, for example, by expressing it as a percentage of GDP. This is the well-known GERD/GDP ratio (Gross Expenditure on R&D relative to GDP). The OECD’s Main Science and Technology Indicators database deliberately includes economic and demographic series so that raw figures can be converted into benchmarks that account for differences in the size of economies, purchasing power, and inflation. Without that contextualisation, comparing a small economy to a large one would be meaningless.

Assessing the health of the scientific enterprise 🔗

The first major function of science indicators is diagnostic. Just as a doctor uses temperature and blood pressure to assess a patient, policy makers use indicators to assess the overall health of the research system. Are investments growing or stagnating? Is the workforce expanding? Is output keeping up with input?

The Indian experience illustrates this well. The Department of Science and Technology (DST) has, through its National Science and Technology Management Information System (NSTMIS), been building an information base on resources devoted to S&T activities since 1973. These surveys generate the indicators that reveal whether the scientific enterprise is thriving. For instance, the R&D statistics showed that gross expenditure on R&D tripled between 2008 and 2018, with publications rising to place the country among the world leaders by volume.

Inputs and outputs 🔗

Indicators are usually grouped into input indicators and output indicators. Input indicators measure the resources poured into research: money, people, and infrastructure. Financial and human resources are treated as the principal inputs to R&D and are used as indicators of the status of the R&D effort in any country. Output indicators measure what comes out the other end: publications, patents, citations, and new products. The common targets of measurement, as the OECD lists them, include human capital, R&D investment, the outputs attributable to those investments, and the patterns of collaboration and knowledge circulation.

Revealing trends over time and across borders 🔗

A second crucial function is the detection of trends. A snapshot is useful, but science indicators become far more powerful when tracked over time. They show whether a field is rising or declining, whether a country is gaining ground on its peers, and where new areas of strength are emerging.

This is why agencies emphasise consistency. Japan’s National Institute of Science and Technology Policy explains that it focuses on basic indicators updated each year specifically to enable time-series comparison as well as international comparison among major countries. The OECD’s flagship database similarly exists to monitor key trends in S&T performance across countries over time.

International benchmarking 🔗

Trends only become meaningful when measured against others. Science indicators allow nations to benchmark themselves internationally. Indian R&D statistics, for example, routinely compare the country against the other BRICS economies, noting that R&D spending stood at 0.64% of GDP in 2020-21, compared with China’s 2.4% and Brazil’s 1.3%. This kind of comparison immediately highlights where a country stands and where it needs to improve. For this benchmarking to be valid, definitions must be standardised, which is why DST adopts UNESCO and OECD guidelines, particularly the concepts laid out in the Frascati Manual, when collecting its data.

Guiding the allocation of scarce resources 🔗

Research funding is finite, and demands always exceed available budgets. A core function of science indicators is to guide where limited resources should go. Because scientific research needs huge investments and calls for the judicious utilisation of scarce resources, the data on where money is being spent, and to what effect, becomes essential for rational planning.

Indicators help here in two ways. First, they reveal which fields are growing and may deserve more support to keep pace with global developments. If publication and patent data show a surge in a strategically important area, that signals where infrastructure and funding should follow. Second, they expose gaps, the areas of concern that need strengthening, allowing decision-makers to redirect effort before problems become entrenched.

Performance-based funding 🔗

In many countries, indicators have moved from informing funding to actively determining it. Researchers reviewing bibliometric evaluation note that tight public budgets have pushed many governments to shift from funding based on institutional size to funding based on research performance. These research assessment exercises pursue several goals at once: stimulating efficiency, allocating funds selectively, reducing information gaps between those who supply and those who demand knowledge, informing strategy, and demonstrating that public investment delivers real benefits. The British Research Assessment Exercise, which has shaped university funding since 1992, is a landmark example of publications and citations being used as feedback parameters in finance schemes.

Helping policy makers make decisions 🔗

All of the functions above converge on a single purpose: supporting decision-making. This is where the idea of evidence-based policymaking comes in. Rather than relying on intuition or political pressure alone, policy makers can ground their choices in data about what is actually happening in the research system.

DST describes its national R&D indicators report as an extraordinarily important document for evidence-based policymaking and planning across higher education, R&D support, intellectual property, and industrial competitiveness. The same report is treated as a reference source book on science and technology by policy makers, planners, researchers, scientists and technologists both at home and abroad. As demands for accountability in R&D investment grow, NISTEP similarly notes that understanding the outputs of R&D and the processes between investment and output has become an important research challenge.

Accountability and transparency 🔗

Indicators also serve a democratic function. Public money funds a large share of research, and citizens are entitled to know whether it is being spent effectively. The OECD frames sound measurement as a way for policy makers to monitor and evaluate the effectiveness and efficiency of their policies. By making research output visible and measurable, indicators allow funding agencies to demonstrate accountability and justify continued investment.

Measuring the impact of science on society 🔗

Beyond the internal health of the research system, science indicators increasingly try to capture the wider impact of science on the economy and society. Patent counts, for instance, signal how effectively research is being converted into marketable innovations. The growth, performance, and impact of science on society and the economy are themselves treated as indicators of the effectiveness of planning and policy formulation.

This is also where the field is evolving. Researchers studying the future of research evaluation argue that social, technological, economic, environmental, and political factors must increasingly be included and normalised in national and international evaluation systems. Newer indicators try to track contributions to open science and to broader goals such as the United Nations Sustainable Development Goals, reflecting a move beyond simply counting papers.

A word of caution on using indicators well 🔗

For all their power, science indicators must be handled with care. An indicator is a proxy, not the reality itself, and treating a measure as the goal can distort behaviour. Counting publications without regard to quality, for example, can encourage quantity over substance. This is why analysts increasingly favour normalised indicators that control for differences in field and institution size, and why tools used for research evaluation emphasise normalised citation indicators that account for subject area and institution size. Good practice in scientometrics means using a basket of indicators together, interpreting them in context, and never letting a single number make a decision on its own.

What do you think? If you were advising a national funding agency, which would you trust more for deciding where to invest: input indicators like R&D spending, or output indicators like publications and patents? And can the true societal value of basic research ever be fully captured by any indicator at all?

References

1. https://www.nationalacademies.org/read/18606/chapter/4
2. https://www.oecd.org/en/topics/sub-issues/science-technology-and-innovation-indicators.html
3. https://www.oecd.org/en/data/datasets/main-science-and-technology-indicators.html
4. https://dst.gov.in/scientific-programmes/scientific-engineering-research/national-science-technology-management-information-system-nstmis
5. https://dst.gov.in/indias-rd-expenditure-scientific-publications-rise
6. https://dst.gov.in/sites/default/files/Research%20and%20Deveopment%20Statistics%202019-20_0.pdf
7. https://www.nistep.go.jp/en/?page_id=52
8. https://www.nstmis-dst.org/Pdfs/R&D%20Statistics%20at%20a%20Glance,%202022-23.pdf
9. https://arxiv.org/pdf/1811.01635
10. https://arxiv.org/pdf/0911.4298
11. https://dst.gov.in/sites/default/files/R&D%20Statistics%20at%20a%20Glance%202019-20.pdf
12. https://pmc.ncbi.nlm.nih.gov/articles/PMC9448456/
13. https://clarivate.com/academia-government/scientific-and-academic-research/research-funding-analytics/incites-benchmarking-analytics/