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Personal and Ubiquitous Computing

, Volume 21, Issue 2, pp 313–326 | Cite as

Visualizing museum visitors’ behavior: Where do they go and what do they do there?

  • Joel LanirEmail author
  • Tsvi Kuflik
  • Julia Sheidin
  • Nisan Yavin
  • Kate Leiderman
  • Michael Segal
Original Article

Abstract

Museum curators and personnel are interested in understanding what is happening at their museum: what exhibitions and exhibits do visitors attend to, what exhibits visitors spend most time at, what hours of the day are most busy at certain areas in the museum and more. We use automatic tracking of visitors’ position, movements and interaction at the museum to log visitor information. Using this information, we provide an interface that visualizes individual and small group movement patterns, presentations watched, and aggregated information of overall visitor engagement at the museum. We utilized a user centered design approach in which we gathered requirements, iteratively designed and implemented a working prototype and evaluated it with the help of domain experts (museum curators and other museum personnel). We describe our efforts and provide insights from the design and evaluation of our system, and outline how it might be generalized for other indoor domains such as supermarkets or shopping malls.

Keywords

Museum behavior Museum mobile guide Visualization User-centered design 

References

  1. 1.
    Bollo A, Dal Pozzolo L (2005, July) Analysis of visitor behaviour inside the museum: an empirical study. In: Proceedings of the 8th international conference on arts and cultural managementGoogle Scholar
  2. 2.
    Klein HJ (1993) Tracking visitor circulation in museum settings. Environ Behav 25(6):782–800CrossRefGoogle Scholar
  3. 3.
    Yalowitz SS, Bronnenkant K (2009) Timing and tracking: unlocking visitor behavior. Visit Stud 12(1):47–64CrossRefGoogle Scholar
  4. 4.
    Chianese A, Marulli F, Piccialli F, Benedusi P, Jung JE (2016) An associative engines based approach supporting collaborative analytics in the internet of cultural things. Futur Gener Comput Syst 66(1):187–198Google Scholar
  5. 5.
    Chianese A, Piccialli F, Valente I (2015) Smart environments and cultural heritage: a novel approach to create intelligent cultural spaces. J Locat Based Serv 9(3):209–234CrossRefGoogle Scholar
  6. 6.
    Hooper-Greenhill E (2006) Studying visitors. In: Macdonald S (ed) A companion to museum studies. Wiley, pp 362–376Google Scholar
  7. 7.
    Dickenson V (1992) Museum visitor surveys: an overview, 1930–1990. Cultural economics. Springer, Berlin, pp 141–150CrossRefGoogle Scholar
  8. 8.
    Bitgood S (2006) An analysis of visitor circulation: movement patterns and the general value principle. Curator Mus J 49(4):463–475CrossRefGoogle Scholar
  9. 9.
    McManus PM (1989) Oh, yes, they do: How museum visitors read labels and interact with exhibit texts. Curator Mus J 32(3):174–189CrossRefGoogle Scholar
  10. 10.
    Leinhardt G, Knutson K (2004) Listening in on museum conversations. Rowman Altamira, LanhamGoogle Scholar
  11. 11.
    Serrell B (1997) Paying attention: the duration and allocation of visitors’ time in museum exhibitions. Curator Mus J 40(2):108–125CrossRefGoogle Scholar
  12. 12.
    Dodge S, Weibel R, Lautenschutz A (2008) Towards a taxonomy of movement patterns. Inf Vis 7(3–4):240CrossRefGoogle Scholar
  13. 13.
    Andrienko G, Andrienko N, Bak P, Keim D, Kisilevich S, Wrobel S (2011) A conceptual framework and taxonomy of techniques for analyzing movement. J Vis Lang Comput 22(3):213–232CrossRefGoogle Scholar
  14. 14.
    Andrienko N, Andrienko G (2012) Visual analytics of movement: an overview of methods, tools and procedures. Inf Vis 12(1):3–24CrossRefzbMATHGoogle Scholar
  15. 15.
    Harle Robert (2013) A survey of indoor inertial positioning systems for pedestrians. IEEE Commun Surv Tutor 15(3):1281–1293CrossRefGoogle Scholar
  16. 16.
    Curran K, Furey E, Lunney T, Santos J, Woods D, McCaughey A (2011) An evaluation of indoor location determination technologies. J Locat Based Serv 5(2):61–78CrossRefGoogle Scholar
  17. 17.
    Gu Y, Lo A, Niemegeers I (2009) A survey of indoor positioning systems for wireless personal networks. IEEE Commun Surv Tutor 11(1):13–32CrossRefGoogle Scholar
  18. 18.
    Kuflik T, Lanir J, Dim E, Wecker A, Corra M, Zancanaro M, Stock O (2011) Indoor positioning: challenges and solutions for indoor cultural heritage sites. In: Proceedings of the 16th international conference on intelligent user interfaces. ACM, pp 375–378Google Scholar
  19. 19.
    Andrienko G, Andrienko N, Rinzivillo S, Nanni M, Pedreschi D, Giannotti F (2009) Interactive visual clustering of large collections of trajectories. In: IEEE symposium on visual analytics science and technology, VAST 2009. IEEE, pp 3–10Google Scholar
  20. 20.
    Bak P, Mansmann F, Janetzko H, Keim D (2009) Spatiotemporal analysis of sensor logs using growth ring maps. IEEE Trans Vis Comput Graph 15(6):913–920CrossRefGoogle Scholar
  21. 21.
    Girgensohn A, Shipman F, Wilcox L (2008) Determining activity patterns in retail spaces through video analysis. In: Proceedings of the 16th ACM international conference on multimedia. ACM, pp 889–892Google Scholar
  22. 22.
    Chittaro L, Ranon R, Ieronutti L (2006) VU-flow: a visualization tool for analyzing navigation in virtual environments. Special issue on visual analytics. IEEE Trans Vis Comput Graph 12(6):1475–1485CrossRefGoogle Scholar
  23. 23.
    Börner K, Penumarthy S (2003) Social diffusion patterns in three-dimensional virtual worlds. Inf Vis 2(3):182–198CrossRefGoogle Scholar
  24. 24.
    Hoobler N, Humhpreys G, Agrawala M. (2004) Visualizing competitive behaviors in multi-user virtual environments. In: Proceedings of the IEEE visualization conference 2004. IEEE Press, pp 163–170Google Scholar
  25. 25.
    Zancanaro M, Kuflik T, Boger Z, Goren-Bar D, Goldwasser D (2007) Analyzing museum visitors’ behavior patterns. User modeling 2007. Springer, Heidelberg, pp 238–246CrossRefGoogle Scholar
  26. 26.
    Veron E, Levasseur M (1983) Ethnographie de l’exposition. Centre Georges Pompidou, ParisGoogle Scholar
  27. 27.
    Dim E, Kuflik T (2015) Automatic detection of social behavior of museum visitor pairs. ACM Trans Interact Intell Syst 4(4):17Google Scholar
  28. 28.
    Lanir J, Kuflik T, Dim E, Wecker AJ, Stock O (2013) The influence of a location-aware mobile guide on museum visitors’ behavior. Interact Comput 25(6):443–460CrossRefGoogle Scholar
  29. 29.
    Kanda T, Shiomi M, Perrin L, Nomura T, Ishiguro H, Hagita N (2007) Analysis of people trajectories with ubiquitous sensors in a science museum. In: IEEE international conference on robotics and automation, 2007. IEEE, pp 4846–4853Google Scholar
  30. 30.
    Lanir J, Bak P, Kuflik T (2014) Visualizing proximity-based spatiotemporal behavior of museum visitors using tangram diagrams. Comput Graph Forum 33(3):261–270CrossRefGoogle Scholar
  31. 31.
    Kuflik T, Wecker AJ, Lanir J, Stock O (2015) An integrative framework for extending the boundaries of the museum visit experience: linking the pre, during and post visit phases. Inf Technol Tour 15(1):17–47CrossRefGoogle Scholar
  32. 32.
    Jeffery SR, Alonso G, Franklin MJ, Hong W, Widom J (2005) A pipelined framework for online cleaning of sensor data streams. Comput SciGoogle Scholar
  33. 33.
    Falk JH, Dierking LD (2012) Museum experience revisited. Left Coast Press, Walnut CreekGoogle Scholar
  34. 34.
    Aoki PM, Grinter RE, Hurst A, Szymanski MH, Thornton JD, Woodruff A (2002) Sotto voce: exploring the interplay of conversation and mobile audio spaces. In: Proceedings of the SIGCHI conference on human factors in computing systems. ACM, pp 431–438Google Scholar
  35. 35.
    Havre S, Hetzler E, Whitney P, Nowell L (2002) Themeriver: visualizing thematic changes in large document collections. IEEE Trans Vis Comput Graph 8(1):9–20CrossRefGoogle Scholar
  36. 36.
    Sykes ER, Pentland S, Nardi S (2015) Context-aware mobile apps using iBeacons: towards smarter interactions. In: Proceedings of the 25th annual international conference on computer science and software engineering. IBM Corp., pp 120–129Google Scholar

Copyright information

© Springer-Verlag London 2016

Authors and Affiliations

  • Joel Lanir
    • 1
    Email author
  • Tsvi Kuflik
    • 1
  • Julia Sheidin
    • 1
  • Nisan Yavin
    • 1
  • Kate Leiderman
    • 1
  • Michael Segal
    • 1
  1. 1.University of HaifaMount Carmel, HaifaIsrael

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