Making Sense of Open Data Statistics with Information from Wikipedia

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8127)


Today, more and more open data statistics are published by governments, statistical offices and organizations like the United Nations, The World Bank or Eurostat. This data is freely available and can be consumed by end users in interactive visualizations. However, additional information is needed to enable laymen to interpret these statistics in order to make sense of the raw data. In this paper, we present an approach to combine open data statistics with historical events. In a user interface we have integrated interactive visualizations of open data statistics with a timeline of thematically appropriate historical events from Wikipedia. This can help users to explore statistical data in several views and to get related events for certain trends in the timeline. Events include links to Wikipedia articles, where details can be found and the search process can be continued. We have conducted a user study to evaluate if users can use the interface intuitively, if relations between trends in statistics and historical events can be found and if users like this approach for their exploration process.


Historical Event Query Expansion Interactive Visualization Line Chart Statistical Visualization 
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. 1.
    Aigner, W., Miksch, S.: Supporting Protocol-Based Care in Medicine via Multiple Coordinated Views. In: Proceedings of the Second International Conference on Coordinated & Multiple Views in Exploratory Visualization, pp. 118–129. IEEE Computer Society, Washington, DC (2004)CrossRefGoogle Scholar
  2. 2.
    Aigner, W., Miksch, S., Müller, W., Schumann, H., Tominski, C.: Visualizing time-oriented data-A systematic view. Comput. Graph. 31(3), 401–409 (2007)CrossRefGoogle Scholar
  3. 3.
    Alonso, O., Baeza-Yates, R., Gertz, M.: Exploratory Search Using Timelines. Presented at the SIGCHI 2007 Workshop on Exploratory Search and HCI Workshop (2007)Google Scholar
  4. 4.
    Auer, S., Bizer, C., Kobilarov, G., Lehmann, J., Cyganiak, R., Ives, Z.G.: DBpedia: A Nucleus for a Web of Open Data. In: Aberer, K., et al. (eds.) ISWC/ASWC 2007. LNCS, vol. 4825, pp. 722–735. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  5. 5.
    Cilibrasi, R.L., Vitanyi, P.M.B.: The Google Similarity Distance. IEEE Trans. Knowl. Data Eng. 19(3), 370–383 (2007)CrossRefGoogle Scholar
  6. 6.
    Fouse, A., Weibel, N., Hutchins, E., Hollan, J.D.: ChronoViz: a system for supporting navigation of time-coded data. In: Tan, D.S., Amershi, S., Begole, B., Kellogg, W.A., Tungare, M. (eds.) CHI Extended Abstracts, pp. 299–304. ACM (2011)Google Scholar
  7. 7.
    Gao, L., Hunter, J.: Publishing, Linking and Annotating Events via Interactive Timelines: an Earth Sciences Case Study. In: Proceedings of the Workhop on Detection, Representation, and Exploitation of Events in the Semantic Web, DeRiVE 2011 (2011)Google Scholar
  8. 8.
    van Hage, W.R., Malaisé, V., Segers, R.H., Hollink, L., Schreiber, G.: Design and use of the Simple Event Model (SEM). Web Semant. Sci. Serv. Agents World Wide Web 9(2), 2 (2011)Google Scholar
  9. 9.
    Heer, J., Viégas, F.B., Wattenberg, M.: Voyagers and voyeurs: supporting asynchronous collaborative information visualization. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1029–1038. ACM, New York (2007)CrossRefGoogle Scholar
  10. 10.
    Hienert, D., Luciano, F.: Extraction of Historical Events from Wikipedia. In: Proceedings of the First International Workshop on Knowledge Discovery and Data Mining Meets Linked Open Data (KNOW@LOD), Heraklion, Greece, pp. 25–36 (2012)Google Scholar
  11. 11.
    Hienert, D., Wegener, D., Paulheim, H.: Automatic Classification and Relationship Extraction for Multi-Lingual and Multi-Granular Events from Wikipedia. In: van Erp, M., van Hage, W.R., Troncy, R., Shamma, D.A. (eds.) Proceedings of the Detection, Representation, and Exploitation of Events in the Semantic Web (DeRiVE 2012), Boston, USA, pp. 1–10 (2012)Google Scholar
  12. 12.
    Hienert, D., Zapilko, B., Schaer, P., Mathiak, B.: Web-Based Multi-View Visualizations for Aggregated Statistics. In: Proceedings of the 5th International Workshop on Web APIs and Service Mashups, pp. 11:1–11:8. ACM, New York (2011)Google Scholar
  13. 13.
    Holzinger, A., Yildirim, P., Geier, M., Simonic, K.-M.: Quality-based knowledge discovery from medical text on the Web Example of computational methods in Web intelligence. In: Pasi, G., Bordogna, G., Jain, L.C. (eds.) Quality Issues in the Management of Web Information. ISRL, vol. 50, pp. 145–158. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  14. 14.
    Jensen, M.: Visualizing Complex Semantic Timelines. NewsBlib. (2003)Google Scholar
  15. 15.
    Kumar, V., Furuta, R., Allen, R.B.: Metadata visualization for digital libraries: interactive timeline editing and review. In: Proceedings of the Third ACM Conference on Digital Libraries, pp. 126–133. ACM, New York (1998)CrossRefGoogle Scholar
  16. 16.
    Kurihara, K., Vronay, D., Igarashi, T.: Flexible timeline user interface using constraints. In: CHI 2005 Extended Abstracts on Human Factors in Computing Systems, pp. 1581–1584. ACM, New York (2005)Google Scholar
  17. 17.
    Marchionini, G.: Exploratory search: from finding to understanding. Commun. ACM 49(4), 41–46 (2006)CrossRefGoogle Scholar
  18. 18.
    Mayr, P., Petras, V.: Cross-concordances: terminology mapping and its effectiveness for information retrieval. CoRR. abs/0806.3765 (2008)Google Scholar
  19. 19.
    Medelyan, O., Milne, D., Legg, C., Witten, I.H.: Mining meaning from Wikipedia. Int. J. Hum.-Comput. Stud. 67(9), 716–754 (2009)CrossRefGoogle Scholar
  20. 20.
    Panchenko, A., Morozova, O.: A study of hybrid similarity measures for semantic relation extraction. In: Proceedings of the Workshop on Innovative Hybrid Approaches to the Processing of Textual Data, pp. 10–18. Association for Computational Linguistics, Stroudsburg (2012)Google Scholar
  21. 21.
    Plaisant, C., Milash, B., Rose, A., Widoff, S., Shneiderman, B.: LifeLines: visualizing personal histories. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 221–227. ACM, New York (1996)Google Scholar
  22. 22.
    Rosling, H.: Visual technology unveils the beauty of statistics and swaps policy from dissemination to access. Stat. J. Iaos J. Int. Assoc. Off. Stat. 24(1-2), 103–104 (2007)Google Scholar
  23. 23.
    Scherp, A., Franz, T., Saathoff, C., Staab, S.: F–a model of events based on the foundational ontology dolce+DnS ultralight. In: Proceedings of the Fifth International Conference on Knowledge Capture, pp. 137–144. ACM, New York (2009)Google Scholar
  24. 24.
    Shaw, R., Troncy, R., Hardman, L.: LODE: Linking Open Descriptions of Events. In: Gómez-Pérez, A., Yu, Y., Ding, Y. (eds.) ASWC 2009. LNCS, vol. 5926, pp. 153–167. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  25. 25.
    Shimabukuro, M.H., Flores, E.F., de Oliveira, M.C.F., Levkowitz, H.: Coordinated Views to Assist Exploration of Spatio-Temporal Data: A Case Study. In: Proceedings of the Second International Conference on Coordinated & Multiple Views in Exploratory Visualization, pp. 107–117. IEEE Computer Society, Washington, DC (2004)CrossRefGoogle Scholar
  26. 26.
    Stab, C., Nazemi, K., Fellner, D.W.: Sematime - timeline visualization of time-dependent relations and semantics. In: Bebis, G., et al. (eds.) ISVC 2010, Part III. LNCS, vol. 6455, pp. 514–523. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  27. 27.
    Voorhees, E.M.: Query expansion using lexical-semantic relations. In: Proceedings of the 17th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 61–69. Springer-Verlag New York, Inc., New York (1994)Google Scholar
  28. 28.
    Wang Baldonado, M.Q., Woodruff, A., Kuchinsky, A.: Guidelines for using multiple views in information visualization. In: Proceedings of the Working Conference on Advanced Visual Interfaces - AVI 2000, Palermo, Italy, pp. 110–119 (2000)Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2013

Authors and Affiliations

  1. 1.GESIS - Leibniz Institute for the Social SciencesCologneGermany

Personalised recommendations