International Journal on Digital Libraries

, Volume 11, Issue 4, pp 239–261 | Cite as

Organization of digital resources as an original facet for exploring the quiescent information capital of a community

  • Guillaume Cabanac
  • Max Chevalier
  • Claude Chrisment
  • Christine Julien


Knowledge workers organize the documents they need for daily task achievement in their personal information spaces (PISs). For a community, people’s PISs constitute in-house value-added resources. Paradoxically, this information source is poorly exploited, as people tend to use external sources (e.g., the Web), although this is probably poorly appropriate in corporate context. This article tackles such information access issues in the common context. Our contribution consists in a faceted visual interface to explore various facets (points of view) of the information of a community, which remains quiescent otherwise. Besides common facets only based on information contents, we propose a new facet relying on the way users in a community manage and organize information. As a result, our approach exploits knowledge workers’ efforts devoted to PIS management, turning them to profit for all, by fostering mutual benefit between stakeholders. The proposed facet relies on an original organization-based similarity measure that we define and experiment.


Information system Personal information space Organization Document Faceted search Knowledge worker Visualization Exploration 


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  1. 1.
    Hinds, P.J., Pfeffer, J.: Why organizations don’t “know what they know”: cognitive and motivational factors affecting the transfer of expertise. In: Ackerman, M.S., Wulf, V., Pipek, V. (eds.) Sharing Expertise: Beyond Knowledge Management, Chap. 1, pp. 3–26. MIT Press, Cambridge (2003). ISBN 0262011956Google Scholar
  2. 2.
    Drucker P.F.: Landmarks of Tomorrow: A Report on the New “Post-Modern” World. Transaction Publishers, New Brunswick (1959)Google Scholar
  3. 3.
    Kidd, A.: The marks are on the knowledge worker. In: CHI’94: Proceedings of the SIGCHI conference on human factors in computing systems, pp. 186–191, New York, NY, USA (1994). ACM. ISBN 0-89791-650-6. doi: 10.1145/191666.191740
  4. 4.
    Sellen A.J., Harper R.H.R.: The Myth of the Paperless Office. The MIT Press, Cambridge (2003) ISBN 026269283XGoogle Scholar
  5. 5.
    Feldman, S.: The high cost of not finding information. KM World magazine 13(3), March (2004). URL
  6. 6.
    Jones, W., Phuwanartnurak, A.J., Gill, R., Bruce, H.: Don’t take my folders away!: organizing personal information to get things done. In: CHI’05 extended abstracts on Human factors in computing systems, pp. 1505–1508. ACM Press, New York (2005). ISBN 1-59593-002-7. doi: 10.1145/1056808.1056952
  7. 7.
    Jones, W.: How people keep and organize personal information. In: Jones, W., Teevan, J. (eds.) Personal Information Management, Chap. 3, pp. 35–56. University of Washington Press, Seattle (2007). ISBN 978-0-295-98755-2Google Scholar
  8. 8.
    Khoo, C.S.G., Luyt, B., Ee, C., Osman, J., Lim, H.-H., Yong, S.: How users organize electronic files on their workstations in the office environment: a preliminary study of personal information organization behaviour. Inf. Res. 11(2) (2007). URL
  9. 9.
    Rucker J., Polanco M.J.: Siteseer: personalized navigation for the Web. Commun. ACM 40(3), 73–76 (1997). doi: 10.1145/245108.245125 ISSN 0001-0782CrossRefGoogle Scholar
  10. 10.
    Wu, H., Gordon, M.D.: Collaborative filing in a document repository. In: SIGIR’04: Proceedings of the 27th annual international ACM SIGIR conference, pp. 518–519. ACM Press, New York, NY, USA (2004). ISBN 1-58113-881-4. doi: 10.1145/1008992.1009099
  11. 11.
    Wu, H., Gordon, M.D., DeMaagd, K.: Document co-organization in an online knowledge community. In: CHI’04: CHI’04 extended abstracts on Human factors in computing systems, pp. 1211–1214. ACM Press, New York, NY, USA (2004). ISBN 1-58113-703-6. doi: 10.1145/985921.986026
  12. 12.
    Dmitriev, P.A., Eiron, N., Fontoura, M., Shekita, E.: Using annotations in enterprise search. In: WWW’06: proceedings of the 15th international conference on World Wide Web, pp. 811–817. ACM Press, New York, NY, USA (2006). ISBN 1-59593-323-9. doi: 10.1145/1135777.1135900
  13. 13.
    Hammond, T., Hannay, T., Lund, B., Scott, J.: Social bookmarking tools (I): a general review. D-Lib Mag. 11(4) (2005). doi: 10.1045/april2005-hammond
  14. 14.
    Millen, D.R., Feinberg, J., Kerr, B.: Dogear: social bookmarking in the enterprise. In: CHI’06: proceedings of the SIGCHI conference on human factors in computing systems, pp. 111–120. ACM Press, New York, NY, USA (2006). ISBN 1-59593-372-7. doi: 10.1145/1124772.1124792
  15. 15.
    Lund, B., Hammond, T., Flack, M., Hannay, T.: Social bookmarking tools (II): a case study—Connotea. D-Lib Mag. 11(4) (2005). doi: 10.1045/april2005-lund
  16. 16.
    Montaner M., López B., de la Rosa J.L.: A taxonomy of recommender agents on the internet. Artif. Intell. Rev. 19(4), 285–330 (2003). doi: 10.1023/A:1022850703159 CrossRefGoogle Scholar
  17. 17.
    Furnas G.W., Landauer T.K., Gomez L.M., Dumais S.T.: The vocabulary problem in human-system communication. Commun. ACM 30(11), 964–971 (1987). doi: 10.1145/32206.32212 ISSN 0001-0782CrossRefGoogle Scholar
  18. 18.
    Sacco, G.M., Tzitzikas, Y.: Dynamic taxonomies and faceted search: theory, practice, and experience. Springer Publishing Company, Inc. Berlin (2009). ISBN 978-3-64202-358-3Google Scholar
  19. 19.
    Kwasnik B.H.: The role of classification in knowledge representation and discovery. Libr. Trends 48(1), 22–47 (1999)Google Scholar
  20. 20.
    Allen R.B.: The role of classification in knowledge representation and discovery. Electron. Publ. 8(2-3), 247–257 (1995)Google Scholar
  21. 21.
    Koren J., Zhang, Y., Liu, X.: Personalized interactive faceted search. In: WWW’08: proceeding of the 17th international conference on World Wide Web, pp. 477–486. ACM, New York, NY, USA (2008). ISBN 978-1-60558-085-2. doi: 10.1145/1367497.1367562
  22. 22.
    Yee, K.-P., Swearingen, K., Li, K., Hearst, M.: Faceted metadata for image search and browsing. In: CHI’03: proceedings of the SIGCHI conference on human factors in computing systems, pp. 401–408. ACM, New York, NY, USA (2003). ISBN 1-58113-630-7. doi: 10.1145/642611.642681
  23. 23.
    Amitay, E., Carmel, D., Har’El, N., Ofek-Koifman, S., Soffer, A., Yogev, S., Golbandi, N.: Social search and discovery using a unified approach. In: WWW ’09: proceedings of the 18th international conference on World wide web, pp. 1211–1212. ACM, New York, NY, USA (2009). ISBN 978-1-60558-487-4. doi: 10.1145/1526709.1526933
  24. 24.
    Kules, B., Capra, R., Banta, M., Sierra, T.: What do exploratory searchers look at in a faceted search interface? In: JCDL’09: proceedings of the 9th ACM/IEEE-CS joint conference on digital libraries, pp. 313–322. ACM, New York, NY, USA (2009). ISBN 978-1-60558-322-8. doi: 10.1145/1555400.1555452
  25. 25.
    Herman I., Melançon G., Marshall M.S.: Graph visualization and navigation in information visualization: a survey. IEEE Trans. Vis. Comput Graph. 6(1), 24–43 (2000). doi: 10.1109/2945.841119 ISSN 1077-2626CrossRefGoogle Scholar
  26. 26.
    Chen C.: Information Visualization: Beyond the Horizon, 2nd edn. Springer, Berlin (2006) ISBN 184628340XGoogle Scholar
  27. 27.
    Yang Y., Akers L., Klose T., Yang C.B.: Text mining and visualization tools—impressions of emerging capabilities. World Patent Inf. 30(4), 280–293 (2008). doi: 10.1016/j.wpi.2008.01.007 CrossRefGoogle Scholar
  28. 28.
    Fekete, J.-D., Plaisant, C.: Interactive information visualization of a million items. In: INFOVIS’02: proceedings of the IEEE symposium on information visualization, pp. 117–124. IEEE Computer Society, Washington, DC, USA (2002). ISBN 0-7695-1751-X. doi: 10.1109/INFVIS.2002.1173156
  29. 29.
    Johnson, B., Shneiderman, B.: Tree-maps: a space-filling approach to the visualization of hierarchical information structures. In: VIS’91: proceedings of the 2nd conference on visualization, pp. 284–291. IEEE Computer Society Press, Los Alamitos, CA, USA (1991). ISBN 0-8186-2245-8. doi: 10.1109/VISUAL.1991.175815
  30. 30.
    Kohonen T.: Self-Organizing Maps, 3rd edn. Springer, Secaucus (2001) ISBN 3540679219zbMATHCrossRefGoogle Scholar
  31. 31.
    Boyer, M., Canut, M.-F., Chevalier, M., Péninou, A., Sèdes, F.: Cartographie de l’organisation : une approche topologique des connaissances. In: EGC’07: actes des 7e journées Extraction et Gestion des Connaissances, volume RNTI-E-9 of Revue des Nouvelles Technologies de l’Information, pp. 557–568. Cépaduès (2007)Google Scholar
  32. 32.
    Mothe J., Chrisment C., Dousset B., Alaux J.: DocCube: Multi-dimensional visualisation and exploration of large document sets. J. Am. Soc. Inf. Sci. 54(7), 650–659 (2003). doi: 10.1002/asi.10257 CrossRefGoogle Scholar
  33. 33.
    Hubert, G., Mothe, J., Benammar, A., Dkaki, T., Dousset, B., Karouach, S.: Textual document mining using a graphical interface. In: HCI’01: proceedings of the 9th international conference on human computer interaction, vol. 1, pp. 918–922. Lawrence Erlbaum Associates, August (2001). ISBN 0-8058-3607-1Google Scholar
  34. 34.
    Lagus K., Kaski S., Kohonen T.: Mining massive document collections by the WEBSOM method. Inf. Sci. 163(1–3), 135–156 (2004). doi: 10.1016/j.ins.2003.03.017 ISSN 0020-0255CrossRefGoogle Scholar
  35. 35.
    Baeza-Yates R.A., Ribeiro-Neto B.A.: Modern Information Retrieval. ACM Press, New York (1999) ISBN 0-201-39829-XGoogle Scholar
  36. 36.
    Manning C.D., Raghavan P., Schütze H.: Introduction to Information Retrieval. Cambridge University Press, Cambridge (2008) ISBN 978-0521865715zbMATHGoogle Scholar
  37. 37.
    Porter M.F.: An algorithm for suffix stripping. Program 14(3), 130–137 (1980). doi: 10.1108/eb046814 CrossRefGoogle Scholar
  38. 38.
    Salton G., Wong A., Yang C.S.: A vector space model for automatic indexing. Commun. ACM 18(11), 613–620 (1975). doi: 10.1145/361219.361220 zbMATHCrossRefGoogle Scholar
  39. 39.
    Abrams, D., Baecker, R., Chignell, M.: Information archiving with bookmarks: personal web space construction and organization. In: CHI’98: proceedings of the conference on human factors in computing systems, pp. 41–48. ACM Press, New York, NY, USA (1998). ISBN 0-201-30987-4. doi: 10.1145/274644.274651
  40. 40.
    Chevalier, M., Chrisment, C., Julien, C.: Helping people searching the web: toward an adaptive and a social system. In: ICWI’04: proceedings of the 3rd international conference WWW/internet, pp. 405–412. IADIS (2004)Google Scholar
  41. 41.
    Jaczynski, M., Trousse, B.: WWW assisted browsing by reusing past navigations of a group of users. In Smyth, B., Cunningham, P. (eds.) EWCBR, vol. 1488 of LNCS, pp. 160–171. Springer, Berlin (1998). ISBN 3-540-64990-5. doi: 10.1007/BFb0056330
  42. 42.
    Klas, C.-P., Fuhr, N.: A new effective approach for categorizing web documents. In: Proceedings of the 22th BCS-IRSG colloquium on IR research, April (2000)Google Scholar
  43. 43.
    Cabanac, G., Chevalier, M., Chrisment, C., Julien, C.: An original usage-based metrics for building a unified view of corporate documents. In: Wagner, R., Revell, N., Pernul, G. (eds.) DEXA’07: proceedings of the 18th international conference on database and expert systems applications, vol. 4653 of LNCS, pp. 202–212. Springer, September 2007. ISBN 3-540-74467-3. doi: 10.1007/978-3-540-74469-6_21
  44. 44.
    Voorhees, E.M.: Overview of TREC 2001. In: TREC’01: proceedings of the 10th Text REtrieval Conference, 11 (2001)Google Scholar
  45. 45.
    NIST. README file for TREC-9 filtering track collections (2001).
  46. 46.
    Hull, D.: Using statistical testing in the evaluation of retrieval experiments. In: SIGIR’93: proceedings of the 16th annual international ACM SIGIR conference, pp. 329–338. ACM Press, New York, NY, USA (1993). ISBN 0-89791-605-0. doi: 10.1145/160688.160758
  47. 47.
    Hertzum M., Pejtersen A.M.: The information-seeking practices of engineers: searching for documents as well as for people. Inf. Process. Manag. 36(5), 761–778 (2000). doi: 10.1016/S0306-4573(00)00011-X ISSN 0306-4573CrossRefGoogle Scholar
  48. 48.
    Eades P.: A heuristic for graph drawing. Congressus Numerantium 42, 149–160 (1984)MathSciNetGoogle Scholar
  49. 49.
    Fruchterman T.M.J., Reingold E.M.: Graph drawing by force-directed placement. Softw. Pract. Exp. 21(11), 1129–1164 (1991). doi: 10.1002/spe.4380211102 ISSN 0038-0644CrossRefGoogle Scholar
  50. 50.
    Jardine N., van Rijsbergen C.J.: The use of hierarchic clustering in information retrieval. Inform. Stor. Retr. 7(5), 217–240 (1971). doi: 10.1016/0020-0271(71)90051-9 CrossRefGoogle Scholar
  51. 51.
    Maarek Y.S., Ben-Shaul I.: Automatically organizing bookmarks per contents. Comput. Netw. ISDN Syst. 28(7-11), 1321–1333 (1996). doi: 10.1016/0169-7552(96)00024-4 CrossRefGoogle Scholar
  52. 52.
    Kaye, J., Vertesi, J., Avery, S., Dafoe, A., David, S., Onaga, L., Rosero, I., Pinch, T.: To have and to hold: exploring the personal archive. In: CHI’06: proceedings of the conference on human factors in computing systems, pp. 275–284. ACM Press, New York, NY, USA (2006). ISBN 1-59593-372-7. doi: 10.1145/1124772.1124814
  53. 53.
    Jones, W., Bruce, H.: A report on the NSF-sponsored workshop on personal information management, Seattle, WA, 2005. Technical report (2005)Google Scholar
  54. 54.
    Jones W.: Keeping found things found: the study and practice of personal information management. Morgan Kaufmann Publishers, San Francisco (2007)Google Scholar
  55. 55.
    Dumais, S., Cutrell, E., Cadiz, JJ, Jancke, G., Sarin, R., Robbins, D.C.: Stuff I’ve seen: a system for personal information retrieval and re-use. In: SIGIR’03: proceedings of the 26th ACM SIGIR conference on research and development in informaion retrieval, pp. 72–79. ACM, New York, NY, USA (2003). ISBN 1-58113-646-3. doi: 10.1145/860435.860451
  56. 56.
    Whittaker, S.: Personal information management: from consumption to curation. Annu. Rev. Inform. Sci. Technol. 45 (2011)Google Scholar
  57. 57.
    Adar, E., Karger, D., Stein, L.A.: Haystack: per-user information environments. In: CIKM’99: proceedings of the 8th international conference on information and knowledge management, pp. 413–422. ACM, New York, NY, USA (1999). ISBN 1-58113-146-1. doi: 10.1145/319950.323231
  58. 58.
    Chirita, P., Gavriloaie, R., Ghita, S., Nejdl, W., Paiu, R.: Activity based metadata for semantic desktop search. In: Gómez-Pérez, A., Euzenat, J. (eds.) ESCW’05: proceedings of the 2nd European Semantic Web conference, vol. 3532 of LNCS, pp. 199–213. Springer (2005). doi: 10.1007/11431053_30
  59. 59.
    Cutrell, E., Robbins, D., Dumais, S., Sarin, R.: Fast, flexible filtering with Phlat—personal search and organization made easy. In: CHI’06: proceedings of the SIGCHI conference on human factors in computing systems, pp. 261–270. ACM, New York, NY, USA (2006). ISBN 1-59593-372-7. doi: 10.1145/1124772.1124812
  60. 60.
    Lutters, W.G., Ackerman, M.S., Zhou, X.: Group information management. In: Jones, W., Teevan, J. (eds.) Personal Information Management, Chap. 14, pp. 236–248. University of Washington Press, Seattle (2007). ISBN 978-0-295-98755-2Google Scholar
  61. 61.
    Whalen, T., Toms, E., Blustein, J.: File sharing and group information management. In: PIM’08: proceedings of the workshop on personal information management (2008)Google Scholar
  62. 62.
    Erickson T.: From PIM to GIM: personal information management in group contexts. Commun. ACM 49(1), 74–75 (2006). doi: 10.1145/1107458.1107495 ISSN 0001-0782CrossRefGoogle Scholar
  63. 63.
    Lagus, K., Honkela, T., Kaski, S., Kohonen, T.: Self-organizing maps of document collections: A new approach to interactive exploration. In: Evangelios, S., Jiawei, H., Usama, F. (eds.) KDD’96: proceedings of the 2nd international conference on knowledge discovery and data mining, pp. 238–243. AAAI Press, Menlo Park California (1996)Google Scholar
  64. 64.
    Andrews K., Kienreich W., Sabol V., Becker J., Droschl G., Kappe F., Granitzer M., Auer P., Tochtermann K.: The InfoSky visual explorer: exploiting hierarchical structure and document similarities. Inf. Vis. 1(3–4), 166–181 (2002). doi: 10.1057/palgrave.ivs.9500023 CrossRefGoogle Scholar
  65. 65.
    Evequoz, F., Lalanne, D.: Personal information management through interactive visualizations. In: Infovis-DC’07: proceedings of the doctoral colloquium of IEEE information visualization conference, pp. 158–160 (2007)Google Scholar
  66. 66.
    Bloehdorn, S., Goerlitz, O., Schenk, S., Voelkel, M.: TagFS—tag semantics for hierarchical file systems. In: I-KNOW’06: proceedings of the 6th international conference on knowledge management, September (2006)Google Scholar
  67. 67.
    Hubmann-Haidvogel A., Scharl A., Weichselbraun A.: Multiple coordinated views for searching and navigating web content repositories. Inf. Sci. 179(12), 1813–1821 (2009). doi: 10.1016/j.ins.2009.01.030 ISSN 0020-0255CrossRefGoogle Scholar
  68. 68.
    Jeh, G., Widom, J.: SimRank: a measure of structural-context similarity. In: KDD’02: proceedings of the 8th ACM SIGKDD international conference on knowledge discovery and data mining, pp. 538–543. ACM, New York, NY, USA (2002). ISBN 1-58113-567-X. doi: 10.1145/775047.775126
  69. 69.
    Hotho, A., Jäschke, R., Schmitz, C., Stumme, G.: FolkRank: a ranking algorithm for folksonomies. In: FGIR’06: proceedings of the workshop on information retrieval, pp. 111–114 (2006)Google Scholar
  70. 70.
    Millan M., Trujillo M., Ortiz E. (2007) A collaborative recommender system based on asymmetric user similarity. In: Hujun, Y., Peter, T., Emilio, C., Will, B., Xin, Y. (eds.) IDEAL’07: proceedings of the 8th international conference on intelligent data engineering and automated learning, vol. 4881 of LNCS. Springer, pp. 663–672 doi: 10.1007/978-3-540-77226-2_67
  71. 71.
    Ahlberg, C., Williamson, C., Shneiderman, B.: Dynamic queries for information exploration: an implementation and evaluation. In: CHI’92: proceedings of the SIGCHI conference on human factors in computing systems, pp. 619–626. ACM, New York, NY, USA (1992). ISBN 0-89791-513-5. doi: 10.1145/142750.143054
  72. 72.
    Mothe, J., Chrisment, C., Dkaki, T., Dousset, B., Egret, D.: Information mining: use of the document dimensions to analyse interactively a document set. In: ECIR’01: proceedings of the European colloquium on IR research, pp. 66–77. BCS, April (2001)Google Scholar
  73. 73.
    Millen, D.R., Fontaine, M.A.: Improving individual and organizational performance through communities of practice. In: GROUP’03: proceedings of the international conference on supporting group work, pp. 205–211. ACM Press, New York, NY, USA (2003). ISBN 1-58113-693-5. doi: 10.1145/958160.958192
  74. 74.
    Gerken J., Heilig M., Jetter H.-C., Rexhausen S., Demarmels M., König W.A., Reiterer H.: Lessons learned from the design and evaluation of visual information-seeking systems. Int. J. Dig. Libr. 10(2–3), 49–66 (2009). doi: 10.1007/s00799-009-0052-6 ISSN 1432-5012CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • Guillaume Cabanac
    • 1
  • Max Chevalier
    • 1
  • Claude Chrisment
    • 1
  • Christine Julien
    • 1
  1. 1.Computer Science DepartmentUniversity of Toulouse, IRIT UMR 5505 CNRSToulouse Cedex 9France

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