Advertisement

Exploring Large Digital Library Collections Using a Map-Based Visualisation

  • Mark Hall
  • Paul Clough
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8092)

Abstract

In this paper we describe a novel approach for exploring large document collections using a map-based visualisation. We use hierarchically structured semantic concepts that are attached to the documents to create a visualisation of the semantic space that resembles a Google Map. The approach is novel in that we exploit the hierarchical structure to enable the approach to scale to large document collections and to create a map where the higher levels of spatial abstraction have semantic meaning. An informal evaluation is carried out to gather subjective feedback from users. Overall results are positive with users finding the visualisation enticing and easy to use.

Keywords

Digital Library Document Collection Delaunay Triangulation Multi Dimensional Scaling System Usability Scale 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Andrews, K., Gutl, C., Moser, J., Sabol, V., Lackner, W.: Search result visualisation with xfind. In: Proceedings of Second International Workshop on User Interfaces to Data Intensive Systems, UIDIS 2001. IEEE Computer Society (2001)Google Scholar
  2. 2.
    Butavicius, M.A., Lee, M.D.: An empirical evaluation of four data visualization techniques for displaying short news text similarities. International Journal of Human-Computer Studies 65(11), 931–944 (2007)CrossRefGoogle Scholar
  3. 3.
    Carey, M., Heesch, D., Rüger, S.: Info navigator: A visualization tool for document searching and browsing. In: 9th International Conference on Distributed Multimedia Systems (DMS) (March 2003)Google Scholar
  4. 4.
    Çöltekin, A., Heil, B., Garlandini, S., Fabrikant, S.I.: Evaluating the effectiveness of interactive map interface designs: A case study integrating usability metrics with eye-movement analysis. Cartography and Geographic Information Science 36(1), 5–17 (2009)CrossRefGoogle Scholar
  5. 5.
    Chen, C., Cribbin, T., Kuljis, J., Macredie, R.: Footprints of information foragers: Behaviour semantics of visual exploration. International Journal of Human-Computer Studies 57(2), 139–163 (2002)CrossRefGoogle Scholar
  6. 6.
    Delaunay, B.: Sur la sphère vide. Izvestia Akademii Nauk SSSR, Otdelenie Matematicheskikh i Estestvennykh Nauk 7, 793–800 (1934)Google Scholar
  7. 7.
    Egenhofer, M.J., Mark, D.M.: Naive geography. In: Kuhn, W., Frank, A.U. (eds.) COSIT 1995. LNCS, vol. 988, pp. 1–15. Springer, Heidelberg (1995)Google Scholar
  8. 8.
    Fabrikant, S.I., Montello, D.R., Mark, D.M.: The natural landscape metaphor in information visualization: The role of commonsense geomorphology. Journal of the American Society for Information Science and Technology 61, 253–270 (2010)Google Scholar
  9. 9.
    Forsell, C., Johansson, J.: An heuristic set for evaluation in information visualization. In: Proceedings of the International Conference on Advanced Visual Interfaces, AVI 2010, pp. 199–206. ACM, New York (2010)CrossRefGoogle Scholar
  10. 10.
    Greene, S., Marchionini, G., Plaisant, C., Shneiderman, B.: Previews and overviews in digital libraries: Designing surrogates to support visual information seeking. Journal of the American Society for Information Science and Technology 51(4), 380–393 (2000)CrossRefGoogle Scholar
  11. 11.
    Hall, M.M., Clough Paul, D., Fernando, S., Stevenson, M., Soroa, A., Aguirre, E.: Automatic generation of hierarchies for exploring digital library collections (forthcoming)Google Scholar
  12. 12.
    Hearst, M.A.: Clustering versus faceted categories for information exploration. Communications of the ACM 49(4), 59–61 (2006)CrossRefGoogle Scholar
  13. 13.
    Hearst, M.A.: Search User Interfaces, 1st edn. Cambridge University Press, New York (2009)CrossRefGoogle Scholar
  14. 14.
    Herrmannova, D., Knoth, P.: Visual search for supporting content exploration in large document collections. D-Lib Magazine 18(7/8) (2012)Google Scholar
  15. 15.
    Hornbæk, K., Hertzum, M.: The notion of overview in information visualization. International Journal of Human-Computer Studies 69(7-8), 509–525 (2011)CrossRefGoogle Scholar
  16. 16.
    Kruskal, J.B.: Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis. Psychometrika 29(1), 1–27 (1964)MathSciNetzbMATHCrossRefGoogle Scholar
  17. 17.
    Kuhn, A., Erni, D., Nierstrasz, O.: Embedding spatial software visualization in the ide: An exploratory study. In: Proceedings of the 5th International Symposium on Software Visualization, SOFTVIS 2010, pp. 113–122. ACM, New York (2010)Google Scholar
  18. 18.
    Lagus, K., Kaski, S., Kohonen, T.: Mining massive document collections by the websom method. Information Sciences, 163(1-3), 135 – 156 (2004), Soft Computing Data Mining Google Scholar
  19. 19.
    Lam, H., Bertini, E., Isenberg, P., Plaisant, C., Carpendale, S.: Seven guiding scenarios for information visualization evaluation. Technical report, Department of Computer Science, University of Calgary (2011)Google Scholar
  20. 20.
    Liew, C.L.: Online cultural heritage exhibitions: A survey of information retrieval features. Program: Electronic Library and Information Systems 39(1), 4–24 (2005)CrossRefGoogle Scholar
  21. 21.
    Marchionini, G.: Exploratory search: From finding to understanding. Communications of the ACM 49(4), 41–46 (2006)CrossRefGoogle Scholar
  22. 22.
    Mashima, D., Kobourov, S.G., Hu, Y.: Visualizing dynamic data with maps. In: Proceedings of the 2011 IEEE Pacific Visualization Symposium, PACIFICVIS 2011, pp. 155–162. IEEE Computer Society, Washington, DC (2011)CrossRefGoogle Scholar
  23. 23.
    Milne, D.N., Witten, I.H., Nichols, D.M.: A knowledge-based search engine powered by wikipedia. In: Proceedings of the Sixteenth ACM Conference on Conference on Information and Knowledge Management, pp. 445–454. ACM (2007)Google Scholar
  24. 24.
    Newton, G., Callahan, A., Dumontier, M.: Semantic journal mapping for search visualization in a large scale article digital library. In: Second Workshop on Very Large Digital Libraries at ECDL 2009 (2009)Google Scholar
  25. 25.
    Olsen, K.A., Korfhage, R.R., Sochats, K.M., Spring, M.B., Williams, J.G.: Visualization of a document collection: The vibe system. Information Processing & Management 29(1), 69–81 (1993)CrossRefGoogle Scholar
  26. 26.
    Pampalk, E., Rauber, A., Merkl, D.: Content-based organization and visualization of music archives. In: Proceedings of the Tenth ACM International Conference on Multimedia, MULTIMEDIA 2002, pp. 570–579. ACM, New York (2002)CrossRefGoogle Scholar
  27. 27.
    Pirolli, P., Schank, P., Hearst, M.A., Diehl, C.: Scatter/gather browsing communicates the topic structure of a very large text collection. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems: Common Ground, pp. 213–220. ACM (1996)Google Scholar
  28. 28.
    Pirolli, P.: Powers of 10: Modeling complex information-seeking systems at multiple scales. Computer 42(3), 33–40 (2009)CrossRefGoogle Scholar
  29. 29.
    Plaisant, C.: The challenge of information visualization evaluation. In: Proceedings of the Working Conference on Advanced Visual Interfaces, AVI 2004, pp. 109–116. ACM, New York (2004)CrossRefGoogle Scholar
  30. 30.
    Rao, R., Pedersen, J.O., Hearst, M.A., Mackinlay, J.D., Card, S.K., Masinter, L., Halvorsen, P.-K., Robertson, G.C.: Rich interaction in the digital library. Communications of the ACM 38(4), 29–39 (1995)CrossRefGoogle Scholar
  31. 31.
    Shiri, A.A., Revie, C., Chowdhury, G.: Thesaurus-enhanced search interfaces. Journal of Information Science 28(2), 111–122 (2002)CrossRefGoogle Scholar
  32. 32.
    Shneiderman, B., Feldman, D., Rose, A., Grau, X.F.: Visualizing digital library search results with categorical and hierarchical axes. In: Proceedings of the Fifth ACM Conference on Digital Libraries, pp. 57–66. ACM (2000)Google Scholar
  33. 33.
    Singer, G., Norbisrath, U., Lewandowski, D.: Ordinary search engine users carrying out complex search tasks. Journal of Information Science (2012)Google Scholar
  34. 34.
    Stoica, E., Hearst, M.A., Richardson, M.: Automating creation of hierarchical faceted metadata structures. In: Human Language Technologies: The Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-HLT 2007), pp. 244–251 (2007)Google Scholar
  35. 35.
    Westerman, S.J., Cribbin, T.: Mapping semantic information in virtual space: dimensions, variance and individual differences. International Journal of Human-Computer Studies 53(5), 765–787 (2000)zbMATHCrossRefGoogle Scholar
  36. 36.
    White, R.W., Kules, B., Drucker, S.M., Schraefel, M.C.: Introduction. Communications of the ACM 49(4), 36–39 (2006)CrossRefGoogle Scholar
  37. 37.
    Yu, J., Thom, J.A., Tam, A.: Ontology evaluation using wikipedia categories for browsing. In: Proceedings of the Sixteenth ACM Conference on Information and Knowledge Management, pp. 223–232. ACM (2007)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Mark Hall
    • 1
  • Paul Clough
    • 2
  1. 1.Department for Computer ScienceUniversity of SheffieldSheffieldUK
  2. 2.Information SchoolUniversity of SheffieldSheffieldUK

Personalised recommendations