Dataset artefacts can partially drive the measured decline in disruption

This figure displays the average CD₅ index over time for six data sources and five different patent categories. The data sources are JSTOR (1,588,088 papers), the American Physical Society corpus (461,359 papers), Microsoft Academic Graph (random sample of 1,000,000 papers), and PubMed (1,563,211 papers). For reference, the Web of Science (22,479,429 papers) and PatentsView (2,926,923 patents) data sources are also included. The patent categories are Chemical (517,964 patents), Computers and communications (748,849 patents), Drugs and medical (321,449 patents), Electrical and electronic (734,769 patents), and Mechanical (603,892 patents). Shaded bands correspond to 95% confidence intervals. a, The temporal evolution of the average CD₅ index for different data sources as presented in Park et al.¹ (Extended Data Fig. 6 in¹). b, When dropping the outliers with CD₅ = 1, the decline in disruptiveness reduces by 100%, 107%, 100%, and 61% for JSTOR, the American Physical Society corpus, Microsoft Academic Graph, and PubMed, from −0.16, −0.27, −0.31, and −0.18 with outliers (panel a, 2006 vs. 1930 for JSTOR, 2010 vs. 1930 otherwise) to −0.00, +0.02, −0.00, and −0.07 without (panel b, 2006 vs. 1930 for JSTOR, 2010 vs. 1930 otherwise), respectively. c, The time evolution of the average CD₅ index for different patent categories as presented in Park et al.¹ (Fig. 2b in¹). d, When dropping the outliers with CD₅ = 1, the decline in disruptiveness reduces by 70%, 58%, 69%, 63 % and 71% for Chemical, Computers and communications, Drugs and medical, Electrical and electronic, and Mechanical patents, from −0.33, −0.24, −0.35, −0.32, and −0.38 with outliers (panel c, 2010 vs. 1980) to −0.10, −0.10, −0.11, −0.12, and −0.11 without (panel d, 2010 vs. 1980), respectively.