Scientific knowledge is growing at a linear rate despite an exponential increase in publications. That’s according to a study by physicists in China and the US, who say their finding points to a decline in overall scientific productivity. The study therefore contradicts the notion that productivity and knowledge grow hand in hand – but adds weight to the view that the rate of scientific discovery may be slowing or that “information fatigue” and the vast number of papers can drown out new discoveries.
Defining knowledge is complex, but it can be thought of as a network of interconnected beliefs and information. To measure it, the authors previously created a knowledge quantification index (KQI). This tool uses various scientific impact metrics to examine the network structures created by publications and their citations and quantifies how well publications reduce the uncertainty of the network, and thus knowledge.
The researchers claim the tool’s effectiveness has been validated through multiple approaches, including analysing the impact of work by Nobel laureates.
In the latest study, published on arXiv, the team analysed 213 million scientific papers, published between 1800 and 2020, as well as 7.6 million patents filed between 1976 and 2020. Using the data, they built annual snapshots of citation networks, which they then scrutinised with the KQI to observe changes in knowledge over time.
The researchers – based at Shanghai Jiao Tong University in Shanghai, the University of Minnesota in the US and the Institute of Geographic Sciences and Natural Resources Research in Beijing –found that while the number of publications has been increasing exponentially, knowledge has not.
Instead, their KQI suggests that knowledge has been growing in a linear fashion. Different scientific disciplines do display varying rates of knowledge growth, but they all have the same linear growth pattern. Patent growth was found to be much slower than publication growth but also shows the linear growth in the KQI.
According to the authors, the analysis indicates “no significant change in the rate of human knowledge acquisition”, suggesting that our understanding of the world has been progressing at a steady pace.
If scientific productivity is defined as the number of papers required to grow knowledge, this signals a significant decline in productivity, the authors claim.
The analysis also revealed inflection points associated with new discoveries, major breakthroughs and other important developments, with knowledge growing at different linear rates before and after.
Such inflection points create the illusion of exponential knowledge growth due to the sudden alteration in growth rates, which may, according to the study authors, have led previous studies to conclude that knowledge is growing exponentially.
Research focus
“Research has shown that the disruptiveness of individual publications – a rough indicator of knowledge growth – has been declining over recent decades,” says Xiangyi Meng, a physicist at Northwestern University in the US, who works in network science but was not involved in the research. “This suggests that the rate of knowledge growth must be slower than the exponential rise in the number of publications.”
Meng adds, however, that the linear growth finding is “surprising” and “somewhat pessimistic” – and that further analysis is needed to confirm if knowledge growth is indeed linear or whether it “more likely, follows a near-linear polynomial pattern, considering that human civilization is accelerating on a much larger scale”.
Due to the significant variation in the quality of scientific publications, Meng says that article growth may “not be a reliable denominator for measuring scientific efficiency”. Instead, he suggests that analysing research funding and how it is allocated and evolves over time might be a better focus.
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