Patent sleeping beauties: evolutionary trajectories and identification methods

  • Jianhua HouEmail author
  • Xiucai Yang


Sleeping Beauties in Science have attracted a lot of attention in scientometrics and beyond. However, sleeping beauties also appear in patent. In this paper, we put forward the concept of patent sleeping beauties. Since the evolution trajectory of patents after public announcement includes citation, transformation and license, we have defined the evolution trajectories of patents through three indicators including early sudden awakening (the “Flash in the pan”), early gradual awakening (the “Pea Princess”), delay gradual awakening (the “Ugly Duckling”), delay sudden awakening (the “sleeping beauty”) and sleeping patent. Furthermore, this paper constructs a quantitative model to identify patent sleeping beauties. Taking the graphene technology patent of China as an example, this paper identified the patent sleeping beauties in graphene technology, and found that the number of sleeping beauty patents accounted for only 0.59% of all patents. In the aspect of patent awakening mode, the awakening of patents with gradual awakening is mainly caused by both cited and transferred or cited and licensed. However, both the flash-in-the-pan and the sleeping beauty patents are mainly caused by transferring or licensing single factor. At the same time, through investigation, we found that patent invalidation will not hinder patent awakening, patent awakening will extend the effective life of patents. At last, we provide policy implications for researchers and managers.


Patent sleeping beauties Patent evolution trajectory Patent active life Awakening mode 



The author acknowledges the support of the National Social Science Foundation of China (Award Number # 17BGL031). We would like to express Special thanks to the reviewers. Their comments and suggestions have helped improve the content of the present paper.


  1. Aichouchi, A. E., & Gorry, P. (2018). Delayed recognition of judah folkman’s hypothesis on tumor angiogenesis: When a prince awakens a sleeping beauty by self-citation. Scientometrics, 116(1), 385–399.Google Scholar
  2. Aversa, E. S. (1985). Citation patterns of highly cited papers and their relationship to literature aging: A study of the working literature. Scientometrics, 7(3–6), 383–389.Google Scholar
  3. Avramescu, A. (1979). Actuality and obsolescence of scientific literature. Journal of the American Society for Information Science, 30(5), 296–303.Google Scholar
  4. Barber, B. (1961). Resistance by scientist to scientific discovery. Science, 134, 596–602.Google Scholar
  5. Baumgartner, S. E., & Leydesdorff, L. (2014a). Group-based trajectory modeling (GBTM) of citations in scholarly literature: Dynamic qualities of “transient” and “sticky knowledge claims”. Journal of the Association for Information Science and Technology, 65(4), 797–811.Google Scholar
  6. Baumgartner, S. E., & Leydesdorff, L. (2014b). Group-based trajectory modeling (gbtm) of citations in scholarly literature: Dynamic qualities of “transient” and “sticky knowledge claims”. Journal of the American Society for Information Science and Technology, 65(4), 797–811.Google Scholar
  7. Bornmann, L., Ye, Y. A., & Ye, F. Y. (2018). ‘Identifying “hot papers” and papers with “delayed recognition” in large-scale datasets by using dynamically normalized citation impact scores. Scientometrics, 116(2), 655–674.Google Scholar
  8. Braun, T., Glänzel, W., & Schubert, A. (2010). On sleeping beauties, princes and other tales of citation distributions. Research Evaluation, 19(3), 195–202.Google Scholar
  9. Burrell, Q. L. (2005). Are “sleeping beauties” to be expected? Scientometrics, 65(3), 381–389.Google Scholar
  10. Colavizza, Z., & Francechet, M. (2016). Clustering citation histories in the physical review. Journal of Informetrics, 10(4), 1037–1051.Google Scholar
  11. Comins, J. A., & Leydesdorff, L. (2016). Rpys I/O: Software demonstration of a web-based tool for the historiography and visualization of citation classics, sleeping beauties and research fronts. Scientometrics, 107(3), 1509–1517.Google Scholar
  12. Costas, R., Leeuwen, T. N. V., & Raan, A. F. J. V. (2010). Is scientific literature subject to a ‘sell-by-date’? a general methodology to analyze the ‘durability’ of scientific documents. Journal of the American Society for Information Science and Technology, 61(2), 329–339.Google Scholar
  13. Dalen, H. P. V., & Henkens, K. (2005). Signals in science—on the importance of signaling in gaining attention in science. Scientometrics, 64(2), 209–233.Google Scholar
  14. De Rujula, A., Georgi, H., & Glashow, S. L. (1977). Molecular charmonium: A new spectroscopy? Physical Review Letters, 38(7), 317–321.Google Scholar
  15. Dey, R., Roy, A., Chakraborty, T., & Ghosh, S. (2017). Sleeping beauties in computer science: Characterization and early identification. Scientometrics, 113(5439), 1–19.Google Scholar
  16. Du, J. (2017). A study on systematic identification of “sleeping beauty” publications and on their awaking mechanisms. Dissertation. Nanjing University, Jiangsu, China.Google Scholar
  17. Du, J., & Wu, Y. S. (2016). A bibliometric framework for identifying “princes” who wake up the “sleeping beauty” in challenge-type scientific discoveries. Journal of Data and Information Science, 1(1), 50–68.Google Scholar
  18. Du, J., & Wu, Y. S. (2018). A parameter-free index for identifying under-cited sleeping beauties in science. Scientometrics, 116(2), 959–971.Google Scholar
  19. Egghe, L., Guns, R., & Rousseau, R. (2011). Thoughts on uncitedness: Nobel laureates and fields medalists as case studies. Journal of the American Society for Information Science and Technology, 62(8), 1637–1644.Google Scholar
  20. Fang, H. (2018). Analysing the variation tendencies of the numbers of yearly citations for sleeping beauties in science by using derivative analysis. Scientometrics, 115(2), 1051–1070.Google Scholar
  21. Garfield, E. (1980). Premature Discovery or Delayed Recognition-Why? Current Contents, 21, 5–10.Google Scholar
  22. Garfield, E. (1989a). Delayed recognition in scientific discovery: Citation frequency analysis aids the search for case histories. Current Contents, 23(June 5), 3–9. Reprinted: Essays of an Information Scientist (Vol. 12, pp. 154–160). Philadelphia: ISI Press.Google Scholar
  23. Garfield, E. (1989b). More delayed recognition. Part 1. Examples from the genetics of color blindness, the entropy of short-term memory, phosphoinositides, and polymer Rheology. Current Contents, 38(September 18), 3–8. Reprinted: Essays of an information scientist (Vol. 12, pp. 264–269). Philadelphia: ISI Press.Google Scholar
  24. Garfield, E. (1990). More delayed recognition. Part 2. From inhibin to scanning electron microcopy. Current Contents, 9(February 26), 3–9. Reprinted: Essays of an information scientist (Vol. 13, pp. 68–74). Philadelphia: ISI Press.Google Scholar
  25. Ginsparg, P. H., & Wilson, K. G. (1982). A remnant of chiral symmetry on the lattice. Physical Review D, 25(10), 2649–2657.Google Scholar
  26. Glanzel, W., & Garfield, E. (2004). The myth of delayed recognition. The Scientist, 18(11), 8–9.Google Scholar
  27. Glanzel, W., Schlemmer, B., & Thijs, B. (2003). Better late than never? On the chance to become highly cited only beyond the standard time horizon. Scientometrics, 58(3), 571–586.Google Scholar
  28. Gorry, P., & Ragouet, P. (2016). “Sleeping beauty” and her restless sleep: Charles dotter and the birth of interventional radiology. Scientometrics, 107(2), 773–784.Google Scholar
  29. Ho, Y. S., & Hartley, J. (2017a). Sleeping beauties in psychology. Scientometrics, 110, 301–305.Google Scholar
  30. Ho, Y. S., & Hartley, J. (2017b). Sleeping beauties in psychology. Scientometrics, 110, 1–5.Google Scholar
  31. Hu, Z., & Wu, Y. (2014). Regularity in the time-dependent distribution of the percentage of never-cited papers: An empirical pilot study based on the six journals. Journal of Informetrics, 8, 136–146.Google Scholar
  32. Huang, T. C., Hsu, C., & Ciou, Z. J. (2015). Systematic methodology for excavating sleeping beauty publications and their princes from medical and biological engineering studies. Journal of Medical and Biological Engineering, 35(6), 749–758.Google Scholar
  33. Ke, Q., Ferrara, E., Radicchi, F., & Flammini, A. (2015). Defining and identifying sleeping beauties in science. Proceedings of the National Academy of Sciences of the United States of America, 112(24), 7426.Google Scholar
  34. Lachance, C., & Larivière, V. (2014). On the citation lifecycle of papers with delayed recognition. Journal of Informetrics, 8(4), 863–872.Google Scholar
  35. Li, J. (2014). Citation curves of all-elements-sleeping-beauties: Flash in the pan first and then delayed recognition. Scientometrics, 100(2), 595–601.Google Scholar
  36. Li, J., & Shi, D. (2016). Sleeping beauties in genius work: When were they awakened? Journal of the Association for Information Science and Technology, 67(2), 432–440.Google Scholar
  37. Li, J., Shi, D. B., Zhao, S. X., & Ye, F. Y. (2014). A study of the “heartbeat spectra” for “sleeping beauties”. Journal of Informetrics, 8(3), 493–502.Google Scholar
  38. Li, J., & Ye, F. Y. (2012). The phenomenon of all-elements-sleeping-beauties in scientific literature. Scientometrics, 92(3), 795–799.Google Scholar
  39. Li, J., & Ye, F. Y. (2016). Distinguishing sleeping beauties in science. Scientometrics, 108(2), 821–828.Google Scholar
  40. Ohba, N., & Nakao, K. (2012). Sleeping beauties in ophthalmology. Scientometrics, 93(2), 253–264.Google Scholar
  41. Palomeras, N. (2003). Sleeping patents: Any reason to wake up? IESE Research Papers, 20(35), 1–35.Google Scholar
  42. Ponomarev, I. V., Williams, D. E., Hackett, C. J., Schnell, J. D., & Haak, L. L. (2014). Predicting highly cited papers: A method for early detection of candidate breakthroughs. Technological Forecasting and Social Change, 81(1), 49–55.Google Scholar
  43. Stent, G. S. (1972). Prematurity and uniqueness in scientific discovery. Scientific American, 227(6), 84–93.Google Scholar
  44. Sun, J., Min, C., & Li, J. (2016). A vector for measuring obsolescence of scientific articles. Scientometrics, 107(2), 745–757.Google Scholar
  45. Teixeira, A. A., & Vieira, P. C. (2017). Sleeping beauties and their princes in innovation studies. New York Inc: Springer-Verlag.Google Scholar
  46. van Raan, A. F. J. (2004). Sleeping beauties in science. Scientometrics, 59(3), 467–472.Google Scholar
  47. van Raan, A. F. J. (2015). Dormitory of physical and engineering sciences: Sleeping beauties may be sleeping innovations. PLoS ONE, 10(10), e0139786.Google Scholar
  48. van Raan, A. F. J. (2017). Sleeping beauties cited in patents: Is there also a dormitory of inventions? Scientometrics, 110(3), 1123–1156.Google Scholar
  49. van Raan, A. F. J., & Winnink, J. J. (2018). Do younger sleeping beauties prefer a technological prince? Scientometrics, 114(2), 701–717.Google Scholar
  50. Wang, J. C., Ma, F. C., Chen, M. J., & Rao, Y. Q. (2012). Why and how can “sleeping beauties” be awakened? Electronic Library, 30(1), 5–18.Google Scholar
  51. Ye, F. Y., & Bornmann, L. (2018). “Smart Girls” versus “Sleeping Beauties” in the sciences: The identification of instant and delayed recognition by using the citation angle. Journal of the Association of Information Science and Technology, 69(3), 359–367.Google Scholar
  52. Zhang, L., Xu, K., & Zhao, J. (2017a). Sleeping beauties in meme diffusion. Scientometrics, 112(1), 1–20.Google Scholar
  53. Zhang, R., Wang, J., & Mei, Y. (2017b). Search for evergreens, in science: A functional data analysis. Journal of Informetrics, 11(3), 629–644.Google Scholar

Copyright information

© Akadémiai Kiadó, Budapest, Hungary 2019

Authors and Affiliations

  1. 1.School of Information ManagementSun Yat-sen UniversityGuangzhouChina
  2. 2.College of Economics and ManagementDalian UniversityDalianChina

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