Advertisement

The Emerging Scholarly Brain

  • Michael J. Kurtz
Conference paper
Part of the Astrophysics and Space Science Proceedings book series (ASSSP, volume 1)

Summary

It is now a commonplace observation that human society is becoming a coherent super-organism, and that the information infrastructure forms its emerging brain. Perhaps, as the underlying technologies are likely to become billions of times more powerful than those we have today, we could say that we are now building the lizard brain for the future organism.

Keywords

Recommender System Betweenness Centrality Citation Network Eigenvector Centrality Citation Graph 
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.

Notes

Acknowledgement.

This essay is dedicated to the memory of two extraordinary scientists who showed me great kindness. Peter Ossorio’s work continues to inspire me in several ways. Jim Gray’s (2007) fourth Paradigm is the clearest exposition of how the new science will actually function.

Also Andre Heck has, through the years, provided me, and many others, with venues to discuss the deeper meaning of some current trends. The references to this paper alone list several.

The ADS is funded by NASA Grant NNX09AB39G.

References

  1. Accomazzi, A. (2010) Astronomy 3.0 Style. ArXiv e-prints arXiv:1006.0670.Google Scholar
  2. Alexander, C., Ishikawa, S., and Silverstein, M. (1977) A Pattern Language, New York: Oxford University Press.Google Scholar
  3. Baldwin, J. A., Phillips, M. M., Terlevich, R. (1981) Classification parameters for the emission-line spectra of extragalactic objects. Publications of the Astronomical Society of the Pacific 93, 5-19.ADSCrossRefGoogle Scholar
  4. Barabasi, A-L (2003) Linked, New York: Plume.Google Scholar
  5. Barabasi, A.-L. (2010) Bursts: the hidden pattern behind everything we do, New York: Dutton.Google Scholar
  6. Bollen, J., Van de Sompel, H., Hagberg, A., Bettencourt, L., Chute, R., Rodriguez, M.A., Balakireva, L. (2009a) Clickstream Data Yields High-Resolution Maps of Science, PLoS ONE, 4, e4803ADSCrossRefGoogle Scholar
  7. Bollen, J., Van de Sompel, H., Hagberg, A., Chute, R., Mailund, T. (2009b). A Principal Component Analysis of 39 Scientific Impact Measures. PLoS ONE 4, e6022.ADSCrossRefGoogle Scholar
  8. Bonacich, P. (1972) Factoring and weighting approaches to status scores and clique identification, Journal of Mathematical Sociology 2, 113-120.CrossRefGoogle Scholar
  9. Borgman, C.L. (2007) Scholarship in the Digital Age: Information, Infrastructure, and the Internet, Cambridge: MIT Press.Google Scholar
  10. Brin, S. & Page, L. (1998),The Anatomy of a Large-Scale Hypertextual Web Search Engine, Computer Networks and ISDN Systems, 30, 107.CrossRefGoogle Scholar
  11. Connolly, A. J., Szalay, A. S., Bershady, M. A., Kinney, A. L., Calzetti, D. (1995) Spectral Classification of Galaxies: an Orthogonal Approach. The Astronomical Journal 110, 1071.ADSCrossRefGoogle Scholar
  12. Davis, P.M. (2008) Eigenfactor: Does the Principle of Repeated Improvement Result in Better Estimates than Raw Citation Counts?, Journal of the American Society for Information Science and Technology, 59, 2186.CrossRefGoogle Scholar
  13. Deerwester, S., Dumais, S., Furnas, G., Landauer, T., & Harshman, R. (1990). Indexing by latent semantic analysis. Journal of the American Society for Information Science, 41, 391.CrossRefGoogle Scholar
  14. Fitts, P.M. (1954) The Information Capacity of the Human Motor System in Controlling the Amplitude of Movement, Journal of Experimental Psychology 47, 381-391.CrossRefGoogle Scholar
  15. Fortunato, S. (2010) Community detection in graphs. Physics Reports 486, 75-174.MathSciNetADSCrossRefGoogle Scholar
  16. Fu, K.S. and Bhargava, B.K. (1973) Tree Systems for Syntactic Pattern Recognition, IEEE Transactions on Computers 22, 1087-1099.MathSciNetzbMATHCrossRefGoogle Scholar
  17. Ginsparg, P. (1994) First steps towards electronic research communication, Computers in Physics 8, 390-396.Google Scholar
  18. Girvan, M., Newman, M. E. J. (2002) Community structure in social and biological networks. Proceedings of the National Academy of Science 99, 7821-7826.MathSciNetADSzbMATHCrossRefGoogle Scholar
  19. Golay, M., Mandwewala, N., Bartholdi, P. (1977) Spectral classification of stars with the same colours in intermediate multiband photometry - The concept of photometric ‘star-box’. Astronomy and Astrophysics 60, 181-194.ADSGoogle Scholar
  20. Gray, J. (2007) Jim Gray on eScience: A Transformed Scientific Method, in The Fourth Paradigm, Data-Intensive Scientific Discovery, eds T. Hey, S. Tansley, and K. Tolle, Redmond, Washington: Microsoft Research (2009).Google Scholar
  21. Hanisch, R. J. (2001) ISAIA: Interoperable Systems for Archival Information Access. Virtual Observatories of the Future 225, 130.ADSGoogle Scholar
  22. Heylighten, F. and Bollen, J. (1996) The World-Wide Web as a Super-Brain: from metaphor to model. in Cybernetics and Systems ’96 (ed. R. Trappl), p. 917, Vienna: Austrian Society for Cybernetics.Google Scholar
  23. Hebb, D. O. (1955) Drives and the C.N.S. (Conceptual Nervous System), Psychological Review 62, 243-254.CrossRefGoogle Scholar
  24. Henneken, E. A., Accomazzi, A., Kurtz, M. J., Grant, C. S., Thompson, D., Bohlen, E., Murray, S. S., Rosvall, M., Bergstrom, C. (2009) Exploring the Astronomy Literature Landscape. Astronomical Society of the Pacific Conference Series 411, 384.ADSGoogle Scholar
  25. Henneken, E. A., Kurtz, M. J., Accomazzi, A., Grant, C., Thompson, D., Bohlen, E., Di Milia, G., Luker, J., Murray, S. S. (2010) Finding Your Literature Match – A Recommender System. ArXiv e-prints arXiv:1005.2308.Google Scholar
  26. Höldobler, B. and Wilson, E.O. (1970), The Ants, Cambridge: Belknap Press.Google Scholar
  27. Josang, A, Ismail, R. and Boyd, C (2007) A survey of trust and reputation systems for online service provision, Decision Support Systems 43, 618CrossRefGoogle Scholar
  28. Jung, C.G. (1935) Über die Archetypen des kollektiven Unbewussten, Zürich: Rhein-Verlag.Google Scholar
  29. Klous, S, for the ATLAS collaboration (2010) Event Streaming in the Online System: Real-Time Organization of Atlas Data, report number ATL-DAQ-PROC-2010-017, Geneva: CERN.Google Scholar
  30. Koschützki, D., et al (2005) Centrality Indices, in Network Analysis Methodological Foundations, eds U. Brandes and T. Erlebach, Lecture Notes in Computer Science 3418, Heidelberg: Springer.Google Scholar
  31. Kurtz, M. J. (1982) Automatic spectral classification. Ph.D. Thesis, Hanover: Dartmouth College.Google Scholar
  32. Kurtz, M. J. (1989) Classification and knowledge. in Knowledge Based Systems in Astronomy, Lecture Notes in Physics 329, 91-106.ADSCrossRefGoogle Scholar
  33. Kurtz, M. J. (1992) Second Order Knowledge: Information Retrieval in the Terabyte Era. in Astronomy from Large Databases II, European Southern Observatory Conference and Workshop Proceedings 43, 85.Google Scholar
  34. Kurtz, M. J. (1993) Advice from the Oracle: Really Intelligent Information Retrieval. in Intelligent Information Retrieval: The Case of Astronomy and Related Space Sciences, Astrophysics and Space Science Library (ASSL) 182, 21.Google Scholar
  35. Kurtz, M. J., Karakashian, T., Grant, C. S., Eichhorn, G., Murray, S. S., Watson, J. M., Ossorio, P. G., Stoner, J. L. (1993) Intelligent Text Retrieval in the NASA Astrophysics Data System. in Astronomical Data Analysis Software and Systems II 52, 132.Google Scholar
  36. Kurtz, M. J., Eichhorn, G., Accomazzi, A., Grant, C. S., Murray, S. S., Watson, J. M. (2000) The NASA Astrophysics Data System: Overview. Astronomy and Astrophysics Supplement Series 143, 41-59.ADSCrossRefGoogle Scholar
  37. Kurtz, M. J., Eichhorn, G., Accomazzi, A., Grant, C. S., Murray, S. S. (2002) Second order bibliometric operators in the Astrophysics Data System. Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series 4847, 238-245.Google Scholar
  38. Kurtz, M. J., Eichhorn, G., Accomazzi, A., Grant, C. S., Demleitner, M., Murray, S. S. (2005) Worldwide Use and Impact of the NASA Astrophysics Data System Digital Library. Journal of the American Society for Information Science and Technology 56, 36.ADSCrossRefGoogle Scholar
  39. Kurtz, M. J., Henneken, E. A., Accomazzi, A., Bergstrom, C., Rosvall, M., Grant, C. S., Thompson, D., Bohlen, E., Murray, S. S. (2007) Mapping The Astronomy Literature. Bulletin of the American Astronomical Society 38, 808.ADSGoogle Scholar
  40. Kurtz, M. J., Accomazzi, A., Henneken, E., Di Milia, G., Grant, C. S. (2009) Using Multipartite Graphs for Recommendation and Discovery. ArXiv e-prints arXiv:0912.5235; to appear in Astronomical Data Analysis Software and Systems XIX.Google Scholar
  41. Kurtz, M. J., Bollen, J. (2010) Usage Bibliometrics. Annual Review of Information Science and Technology, 44, 3-64.Google Scholar
  42. Kurzweil, R. (2001) The Law of Accelerating Returns, http://www.kurzweilai.net/the-law-of-accelerating-returns
  43. Lancichinetti, A., Fortunato, S. (2009) Community detection algorithms: A comparative analysis. Physical Review E 80, 056117.ADSCrossRefGoogle Scholar
  44. Leydesdorff, L. (2007) Betweenness centrality as an indicator of the interdisciplinarity of scientific journals.  Journal of the American Society for Information Science and Technology, 58, 1303-1319.CrossRefGoogle Scholar
  45. Metro-Goldwyn-Mayer (1956) Forbidden Planet (film)Google Scholar
  46. Murtagh, F. and Heck, A. (1987) Multivariate Data Analysis, Berlin: Springer Verlag.Google Scholar
  47. Newman, M.E.J. (2003) The structure and function of complex networks, SIAM Review 45, 167.MathSciNetADSzbMATHCrossRefGoogle Scholar
  48. Ossorio, P.G. (1965) Classification Space - A Multivariate Procedure for Automatic Document Indexing and Retrieval, Multivariate Behavioral Research 1, 479.CrossRefGoogle Scholar
  49. Ossorio, P. G. (1967). Attribute space development and evaluation (RADC-TR-67-640), Rome, NY: Rome Air Development Center.Google Scholar
  50. Ossorio, P.G. (1977) “What Actually Happens”, The Representation of Real-World Phenomena, Colombia, South Carolina: University of South Carolina Press.Google Scholar
  51. Pinker, S. (1994) The Language Instinct, New York: William Morrow.Google Scholar
  52. Pinker, S. (1997) How the Mind Works, New York: W. W. Norton.Google Scholar
  53. Rosvall, M., Bergstrom, C. T. (2008) Maps of random walks on complex networks reveal community structure. Proceedings of the National Academy of Science 105, 1118-1123.ADSCrossRefGoogle Scholar
  54. Stapledon, O. (1930) The First and Last Men, London:Methuen.Google Scholar
  55. Szalay, A. and Gray, J. (2001) The World-Wide Telescope, Science 293, 2037-2040.ADSCrossRefGoogle Scholar
  56. Taylor, M., Boch, T., Fitzpatrick, M., Allan, A., Paioro, L., Taylor, J., Tody, D. (2009) SAMP - Simple Application Messaging Protocol, v 1.11, International Virtual Observatory Alliance.Google Scholar
  57. Thurstone, L.L. (1934) Vectors of the Mind, Psychological Review 41, 1.CrossRefGoogle Scholar
  58. Van de Sompel, H., Lagoze, C., Nelson, M. L., Warner, S., Sanderson, R., Johnston, P. (2009) Adding eScience Assets to the Data Web. ArXiv e-prints arXiv:0906.2135.Google Scholar
  59. von Frisch, K. (1967) The Dance Language and Orientation of Bees, Cambridge: Harvard University Press.Google Scholar
  60. Wassermann, S., and Faust, K. (1994) Social Network Analysis, Cambridge (U.K.): Cambridge University Press.Google Scholar
  61. West, J.D., Bergstrom, T.C., Bergstrom, C.T. (2010a) The Eigenfactor Metrics (TM): A Network Approach to Assessing Scholarly Journals, College and Research Libraries, 71, 236.Google Scholar
  62. West, J., Bergstrom, T., Bergstrom, C.T. (2010b) Big Macs and Eigenfactor Scores: Don’t Let Correlation Coefficients Fool You, Journal of the American Society for Information Science and Technology, to appear: (DOI: 10.1002/asi.21374).Google Scholar
  63. Zhao, Y. and Karypis, G. (2004) Empirical and Theoretical Comparisons of Selected Criterion Functions for Document Clustering, Machine Learning, 55, 311-331.zbMATHCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.Harvard-Smithsonian Center for AstrophysicsCambridgeUSA

Personalised recommendations