The Dynamics of Scientific Knowledge

  • Chaomei Chen


The body of scientific knowledge changes all the time. Sometimes the changes are incremental, whereas other times the changes are fundamental. What is the structure of scientific knowledge as a whole? How does it evolve over time? Are there telltale signs when revolutionary changes take place? We set the stage for a broad range and critical review of how these issues have been addressed in the past and how information and computational approaches may help.


Visual Analytic Bovine Spongiform Encephalopathy Scientific Revolution Information Visualization Research Front 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Bernal JD (1939) The social function of science. The Macmillan Co., New YorkGoogle Scholar
  2. Callon M, Law J, Rip A (eds) (1986) Mapping the dynamics of Science and technology: sociology of science in the real world. Macmillan Press, LondonGoogle Scholar
  3. Card SK (1996) Visualizing retrieved information: a survey. IEEE Comput Graph Appl 16(2):63–67CrossRefGoogle Scholar
  4. Card S, Mackinlay J, Shneiderman B (eds) (1999) Readings in information visualization: using vision to think. Morgan Kaufmann, San FranciscoGoogle Scholar
  5. Chalmers M (1992) BEAD: explorations in information visualisation. Paper presented at the SIGIR’92, Copenhagen, Denmark, June 1992Google Scholar
  6. Chen C (1999) Information visualisation and virtual environments. Springer, LondonCrossRefGoogle Scholar
  7. Chen C (2010) Information visualization. Wiley Interdiscip Rev Comput Stat 2(4):387–403CrossRefGoogle Scholar
  8. Crane D (1972) Invisible colleges: diffusion of knowledge in scientific communities. University of Chicago Press, ChicagoGoogle Scholar
  9. Fimmel RO, Allen JV, Burgess E (1980) Pioneer: first to Jupiter, Saturn, and beyond (U.S. Government Printing Office No. NASA SP-446). Scientific and Technical Information Office/NASA, Washington, DCGoogle Scholar
  10. Hearst MA (1999) User interfaces and visualization. In: Baeza-Yates R, Ribeiro-Neto B (eds) Modern information retrieval. Addison-Wesley, Harlow, pp 257–224Google Scholar
  11. Herman I, Melançon G, Marshall MS (2000) Graph visualization and navigation in information visualization: a survey. IEEE Trans Vis Comput Graph 6(1):24–44CrossRefGoogle Scholar
  12. Hollan JD, Bederson BB, Helfman J (1997) Information visualization. In: Helenader MG, Landauer TK, Prabhu P (eds) The handbook of human computer interaction. Elsevier Science, Amsterdam, pp 33–48Google Scholar
  13. Ihde D (1998) Expanding hermeneutics: visualism in science. Northwester University Press, EvanstonGoogle Scholar
  14. Inselberg A (1997) Multidimensional detective. Paper presented at the IEEE InfoVis’97, Phoenix, AZ, October 1997Google Scholar
  15. Keim D, Mansmann F, Schneidewind J, Thomas J, Ziegler H (2008) Visual analytics: scope and challenges. Vis Data Min 4404:76–90CrossRefGoogle Scholar
  16. Kochen M (1984) Toward a paradigm for information science: the influence of Derek de Solla Price. J Am Soc Inf Sci Technol 35(3):147–148CrossRefGoogle Scholar
  17. Kornish LJ, Ulrich KT (2011) Opportunity spaces in innovation: empirical analysis of large samples of ideas. Manag Sci 57(1):170–128CrossRefGoogle Scholar
  18. Kou L, Kou YH (1976) Chinese folktales. 231 Adrian Road, Millbrae, CA 94030: Celestial Arts, pp 83–85Google Scholar
  19. Kuhn TS (1962) The structure of scientific revolutions. University of Chicago Press, ChicagoGoogle Scholar
  20. Latour B (2005) Reassembling the social – an introduction to actor-network-theory. Oxford University Press, OxfordGoogle Scholar
  21. Masterman M (1970) The nature of the paradigm. In: Lakatos I, Musgrave A (eds) Criticism and the growth of knowledge. Cambridge University Press, Cambridge, pp 59–89Google Scholar
  22. McGrath JE, Altman I (1966) Small group research: a synthesis and critique of the field. Holt, Rinehart & Winston, New YorkGoogle Scholar
  23. McKim RH (1980) Experiences in visual thinking, 2nd edn. PWS Publishing Company, BostonGoogle Scholar
  24. Mukherjea S (1999) Information visualization for hypermedia systems. ACM Comput Surv 31(4):U24–U29MathSciNetGoogle Scholar
  25. Norwood RH (1958) Patterns of discovery. Cambridge University Press, CambridgeGoogle Scholar
  26. Price DD (1963) Little science, big science. Columbia University Press, New YorkGoogle Scholar
  27. Price DD (1965) Networks of scientific papers. Science 149:510–515CrossRefGoogle Scholar
  28. Rittschof KA, Stock WA, Kulhavy RW, Verdi MP, Doran JM (1994) Thematic maps improve memory for facts and inferences: a test of the stimulus order hypothesis. Contemp Educ Psychol 19:129–142CrossRefGoogle Scholar
  29. Small H (1977) A co-citation model of a scientific specialty: a longitudinal study of collagen research. Soc Stud Sci 7:139–166CrossRefGoogle Scholar
  30. Small HG, Griffith BC (1974) The structure of scientific literatures I: identifying and graphing specialties. Sci Stud 4:17–40CrossRefGoogle Scholar
  31. Spence B (2000) Information visualization. Addison-Wesley, New YorkGoogle Scholar
  32. Thagard P (1992) Conceptual revolutions. Princeton University Press, PrincetonGoogle Scholar
  33. Thomas JJ, Cook K (2005) Illuminating the path: the R&D agenda for visual analytics. IEEE Computer Society, Los AlamitosGoogle Scholar
  34. Tufte ER (1983) The visual display of quantitative information. Graphics Press, CheshireGoogle Scholar
  35. Tufte ER (1990) Envisioning information. Graphics Press, CheshireGoogle Scholar
  36. Tufte ER (1997) Visual explanations. Graphics Press, CheshireMATHGoogle Scholar
  37. Ware C (2000) Information visualization: perception for design. Morgan Kaufmann Publishers, San FranciscoGoogle Scholar
  38. Wise JA, Thomas JJ, Pennock K, Lantrip D, Pottier M, Schur A, et al (1995) Visualizing the non-visual: spatial analysis and interaction with information from text documents. Paper presented at the IEEE symposium on information visualization’95, Atlanta, Georgia, USA, 30–31 October 1995Google Scholar
  39. Wong PC (2010) The four roads less traveled – a tribute to Jim Thomas (1946–2010). From
  40. Wong P, Thomas J (2004) Visual analytics. IEEE Comput Graph Appl 24(5):20–21CrossRefGoogle Scholar

Copyright information

© Springer-Verlag London 2013

Authors and Affiliations

  • Chaomei Chen
    • 1
  1. 1.College of Information Science and TechnologyDrexel UniversityPhiladelphiaUSA

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