Growth rates of modern science: A bibliometric analysis based on the number of publications and cited references (1402.4578v3)

Abstract: Many studies in information science have looked at the growth of science. In this study, we re-examine the question of the growth of science. To do this we (i) use current data up to publication year 2012 and (ii) analyse it across all disciplines and also separately for the natural sciences and for the medical and health sciences. Furthermore, the data are analysed with an advanced statistical technique - segmented regression analysis - which can identify specific segments with similar growth rates in the history of science. The study is based on two different sets of bibliometric data: (1) The number of publications held as source items in the Web of Science (WoS, Thomson Reuters) per publication year and (2) the number of cited references in the publications of the source items per cited reference year. We have looked at the rate at which science has grown since the mid-1600s. In our analysis of cited references we identified three growth phases in the development of science, which each led to growth rates tripling in comparison with the previous phase: from less than 1% up to the middle of the 18th century, to 2 to 3% up to the period between the two world wars and 8 to 9% to 2012.

• The paper identifies three distinct growth phases in scientific output, with annual rates rising from less than 1% to 8-9%.
• The authors apply segmented regression analysis on publications and cited references to quantify centuries of scientific progress.
• Their findings highlight discipline-specific dynamics that offer actionable insights for science policy and research planning.

Growth Rates of Modern Science: A Bibliometric Analysis

Overview

The paper "Growth rates of modern science: A bibliometric analysis based on the number of publications and cited references" by Lutz Bornmann and Rüdiger Mutz presents an in-depth bibliometric analysis of the growth of scientific research output from the mid-1600s to 2012. Using bibliometric data from the Web of Science (WoS) and advanced statistical techniques, such as segmented regression analysis, the authors explore the historical growth patterns of scientific literature.

Methodology

The paper employs a two-pronged approach:

1. Number of Publications: The analysis uses publications indexed in WoS from 1980 to 2012.
2. Number of Cited References: Cited references from these publications, dating back to 1650, are evaluated to provide a long-term perspective on the growth of scientific literature.

Segmented regression analysis—a technique capable of identifying distinct growth phases—forms the backbone of the analytical framework.

Key Findings

Phases of Growth

The paper identifies three major growth phases in scientific output, each characterized by an increasing growth rate:

• First Phase (1650 to mid-18th century): Characterized by a growth rate of less than 1%, with doubling times of approximately 150 years.
• Second Phase (mid-18th century to between World Wars): Growth rates increase to around 2-3%, with a doubling time of nearly 30 years.
• Third Phase (World War II to 2012): The growth rate escalates to approximately 8-9%, with a doubling time of around 9 years.

Significant Findings

1. Exponential Growth: The analysis confirms that the global scientific publication output grew exponentially at an annual rate of 3% from 1980 to 2012, doubling approximately every 24 years.
2. Long-Term Growth Patterns: The cited references show a robust long-term exponential growth pattern, with significant shifts around industrial and economic milestones, such as the Industrial Revolution and the period around World War I and II.
3. Disciplinary Differences: While the natural sciences and medical sciences show similar growth patterns, subtle differences in growth rates and timelines indicate discipline-specific dynamics.

Methodological Considerations

The use of segmented regression analysis enables the capture of nuanced shifts in growth rates, identifying periods of acceleration and deceleration with high accuracy. This method is said to explain 99% of the total variance in the number of cited references, underscoring its robustness.

Implications

The results have both theoretical and practical implications. Theoretically, the paper advances our understanding of the historical development and dynamics of scientific growth. Practically, these insights can inform science policy, funding decisions, and strategic planning in research institutions. The historical context provided by the findings emphasizes the interconnectedness of scientific growth with broader economic and social developments.

Future Directions

The paper sets the foundation for multiple future research avenues:

• Enhanced Databases: Future research could benefit from more comprehensive databases encompassing earlier scientific contributions.
• Cross-Disciplinary Analysis: Further exploration across various scientific disciplines could illuminate unique growth patterns, thereby aiding targeted policy formation.
• Impact of Emerging Economies: The growing influence of countries like China and India on global scientific output remains a pertinent area for continued paper.

Limitations

The paper acknowledges several limitations:

• Publication as a Metric: Variability in publication practices across disciplines and historical periods poses challenges.
• Database Characteristics: Changes in database coverage over time, particularly in WoS, can impact the results.
• Internal Versus External Factors: The paper predominantly focuses on internal aspects of scientific growth, potentially overlooking significant external influences.

Conclusion

Bornmann and Mutz's analysis provides a robust framework for understanding the historical growth rates of scientific output. By identifying clear phases of growth and quantifying their respective rates, the paper affords a comprehensive view of scientific development over several centuries. The implications extend beyond academia, offering valuable insights for science policy and strategic research management.