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Personal and Ubiquitous Computing

, Volume 22, Issue 4, pp 807–824 | Cite as

Uncover: supporting city exploration with egocentric visualizations of location-based content

  • Tuomas VaittinenEmail author
  • David McGookin
Original Article

Abstract

This paper describes the design and evaluation of Uncover: a mobile application that supports users in exploratory pedestrian behavior to gain situational awareness of their immediate environment. The design was based on guidelines derived from foraging theory and relies on egocentric views, which keep the virtual content automatically aligned with the real world. We carried out two studies with Uncover, which examine the successfulness of design choices aiming to support tourists’ city exploration while interfering with experiencing the surroundings as little as possible. A lab study tested the effect of different marker and background types on the time to recognize the direction with most content. The designs performing best were implemented in the final prototype, and a field study analyzed the exploration behavior tourists and visitors exhibited while using it. The study showed that supporting the exploration can be improved by enabling features that are either disabled by default or not available at all in commercial map applications, like egocentric orientation of the map, providing images of venues just by pointing to their direction, and displaying clusters of several venue types.

Keywords

City exploration Exploratory navigation Location-based content Field study Foraging theory Design 

Notes

Acknowledgements

We thank all participants, as well as Helsinki Tourist Information, Couchsurfing Helsinki, and Aalto Exchange Study Coordinators for helping to recruit them. We are also grateful for the HelsinCHI community for comments in the various phases of the work.

Supplementary material

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References

  1. 1.
    World Tourism Organization (2017) UNWTO tourism highlights, 2017 editionCrossRefGoogle Scholar
  2. 2.
    Allen GL (1998) Spatial abilities, cognitive maps, and wayfinding. In: Golledge RG (ed) Wayfinding Behav. Cogn. Mapp. Other Spat. Process. JHU Press, pp 46–80Google Scholar
  3. 3.
    Brown B (2007) Working the problems of tourism. Ann Tour Res 34:364–383.  https://doi.org/10.1016/j.annals.2006.09.003 CrossRefGoogle Scholar
  4. 4.
    Brown B, McGregor M, Laurier E (2013) iPhone in vivo: video analysis of mobile device use. In: Proc. SIGCHI Conf. Hum. Factors Comput. Syst. (CHI ‘13). ACM Press, New York, pp 1031–1040CrossRefGoogle Scholar
  5. 5.
    Vaittinen T, McGookin D (2016) Phases of Urban Tourists’ Exploratory Navigation. In: Proc. 2016 ACM Conf. Des. Interact. Syst. (DIS ‘16). pp 1111–1122Google Scholar
  6. 6.
    Holland S, Morse DR, Gedenryd H (2002) AudioGPS: spatial audio navigation with a minimal attention interface. Pers Ubiquitous Comput 6:253–259CrossRefGoogle Scholar
  7. 7.
    Jones M, Jones S, Bradley G, Warren N, Bainbridge D, Holmes G (2007) ONTRACK: dynamically adapting music playback to support navigation. Pers Ubiquitous Comput 12:513–525CrossRefGoogle Scholar
  8. 8.
    Komninos A, Barrie P, Stefanis V, Plessas A (2012) Urban exploration using audio scents. In: Proc. 14th Int. Conf. Human-computer Interact. with Mob. devices Serv. (MobileHCI ‘12). ACM Press, New York, pp 349–358CrossRefGoogle Scholar
  9. 9.
    Robinson S, Jones M, Eslambolchilar P, Murray-Smith R, Lindborg M (2010) “I did it my way”: Moving Away from the Tyranny of Turn-by-Turn Pedestrian Navigation. In: Proc. 12th Int. Conf. Hum. Comput. Interact. with Mob. devices Serv. (MobileHCI ‘10). ACM Press, New York, pp 341–344Google Scholar
  10. 10.
    Zhou H, Edrah A, MacKay B, Reilly D (2017) Block Party: Synchronized Planning and Navigation Views for Neighbourhood Expeditions. In: Proc. 2017 CHI Conf. Hum. Factors Comput. Syst. (CHI ‘17). ACM Press, New York, New York, USA, pp 1702–1713Google Scholar
  11. 11.
    Abowd GD, Atkeson CG, Hong J, Long S, Kooper R, Pinkerton M (1997) Cyberguide: a mobile context-aware tour guide. Wirel Netw 3:421–433.  https://doi.org/10.1023/A:1019194325861 CrossRefGoogle Scholar
  12. 12.
    Komninos A, Besharat J, Ferreira D, Garofalakis J (2013) HotCity: enhancing ubiquitous maps with social context heatmaps. Proc 12th Int Conf Mob Ubiquitous Multimed (MUM ‘13).  https://doi.org/10.1145/2541831.2543694
  13. 13.
    Cheverst K, Turner H, Do T, Fitton D (2017) Supporting the consumption and co-authoring of locative media experiences for a rural village community: design and field trial evaluation of the SHARC2.0 framework. Multimed Tools Appl 76:5243–5274.  https://doi.org/10.1007/s11042-016-3515-y CrossRefGoogle Scholar
  14. 14.
    White RW, Marchionini G, Muresan G (2008) Evaluating exploratory search systems: introduction to special topic issue of information processing and management. Inf Process Manag 44:433–436.  https://doi.org/10.1016/j.ipm.2007.09.011 CrossRefGoogle Scholar
  15. 15.
    Stephens DW, Krebs JR (1986) Foraging theory. Princeton University PressGoogle Scholar
  16. 16.
    Pirolli P, Card S (1995) Information foraging in information access environments. In: Proc. SIGCHI Conf. Hum. factors Comput. Syst. (CHI ‘95). ACM Press, New York, pp 51–58CrossRefGoogle Scholar
  17. 17.
    Popescu GV, Trefftz H, Burdea G (2014) Multimodal interaction modeling. In: Hale KS, Stanney KM (eds) Handb. virtual Environ. Des. implementation, Appl., Second Edi. CRC Press, pp 411–434Google Scholar
  18. 18.
    Wen J, Helton WS, Billinghurst M (2013) Classifying users of mobile pedestrian navigation tools. In: Proc. 25th Aust. Comput. Interact. Conf. Augment. Appl. Innov. Collab. - OzCHI ‘13. ACM Press, New York, pp 13–16Google Scholar
  19. 19.
    Quercia D, Schifanella R, Aiello LM (2014) The shortest path to happiness: recommending beautiful, quiet, and happy routes in the City. In: Proc. 25th ACM Conf. Hypertext Soc. media. ACM Press, New York, pp 116–125Google Scholar
  20. 20.
    El Ali A, van Sas SNA, Nack F (2013) Photographer paths: sequence alignment of geotagged photos for exploration-based route planning. In: Proc. 2013 Conf. Comput. Support. Coop. Work (CSCW ‘13). ACM Press, New York, pp 985–994Google Scholar
  21. 21.
    Bilandzic M, Foth M (2012) A review of locative media, mobile and embodied spatial interaction. Int J Hum Comput Stud 70:66–71CrossRefGoogle Scholar
  22. 22.
    Foursquare (2017) Foursquare. https://foursquare.com/. Accessed 2 Feb 2017
  23. 23.
    Cheverst K, Davies N, Mitchell K, Friday A, Efstratiou C (2000) Developing a context-aware electronic tourist guide. In: Proc. SIGCHI Conf. Hum. factors Comput. Syst. (CHI ‘00). ACM Press, New York, pp 17–24CrossRefGoogle Scholar
  24. 24.
    Hornecker E, Swindells S, Dunlop M (2011) A mobile guide for serendipitous exploration of cities. In: Proc. 13th Int. Conf. Hum. Comput. Interact. with Mob. Devices Serv. (MobileHCI ‘11). ACM Press, New York, pp 557–562Google Scholar
  25. 25.
    Stahl C (2007) The Roaring Navigator: A Group Guide for the Zoo with Shared Auditory Landmark Display. In: Proc. 9th Int. Conf. Hum. Comput. Interact. with Mob. devices Serv. (MobileHCI ‘07). ACM Press, New York, pp 383–386Google Scholar
  26. 26.
    Espinoza F, Persson P, Sandin A, Nyström H, Cacciatore E, Bylund M (2001) GeoNotes: social and navigational aspects of location-based information systems. In: Proc. 3rd Int. Conf. Ubiquitous Comput. Springer-Verlag, pp 2–17Google Scholar
  27. 27.
    Burrell J, Gay GK (2002) E-graffiti: evaluating real-world use of a context-aware system. Interact Comput 14:301–312.  https://doi.org/10.1016/S0953-5438(02)00010-3 CrossRefGoogle Scholar
  28. 28.
    Rantanen M, Oulasvirta A, Blom J, Tiitta S, Mäntylä M (2004) InfoRadar: Group and Public Messaging in the Mobile Context. In: 3rd Nord. Conf. Human-computer Interact. ACM, Tampere, pp 131–140Google Scholar
  29. 29.
    Persson P, Fagerberg P (2002) GeoNotes: a real-use study of a public location-aware community system. Swedish Inst. Comput. Sci. Tech. Rep. http://eprints.sics.se/2275/
  30. 30.
    Robinson S, Jones M, Williamson J, Murray-Smith R, Eslambolchilar P, Lindborg M (2011) Navigation your way: from spontaneous independent exploration to dynamic social journeys. Pers Ubiquitous Comput 16:973–985CrossRefGoogle Scholar
  31. 31.
    Kjeldskov J, Paay J (2005) Just-for-us: a context-aware mobile information system facilitating sociality. In: Proc. 7th Int. Conf. Hum. Comput. Interact. with Mob. devices Serv. (MobileHCI ‘05). ACM Press, New York, pp 23–30Google Scholar
  32. 32.
    Paay J, Kjeldskov J, Howard S, Dave B (2009) Out on the town: a socio-physical approach to the design of a context-aware urban guide. ACM Trans Comput Interact 16:1–34.  https://doi.org/10.1145/1534903.1534904 CrossRefGoogle Scholar
  33. 33.
    Weal MJ, Michaelides DT, Thompson MK, DeRoure DC (2003) The ambient wood journals: Replaying the experience. In: Proc. fourteenth ACM Conf. Hypertext hypermedia - HYPERTEXT ‘03. ACM Press, New York, pp 20–27Google Scholar
  34. 34.
    Ballagas RA, Kratz SG, Borchers J, Yu E, Walz SP, Fuhr CO, Hovestadt L, Tann M (2007) REXplorer: a mobile, pervasive spell-casting game for tourists. In: Ext. Abstr. Hum. factors Comput. Syst. (CHI ‘07). ACM Press, New York, pp 1929–1934Google Scholar
  35. 35.
    Herbst I, Braun A-K, McCall R, Broll W (2008) TimeWarp: interactive time travel with a mobile mixed reality game. In: Proc. 10th Int. Conf. Hum. Comput. Interact. with Mob. devices Serv. - MobileHCI ‘08. ACM Press, New York, pp 235–244Google Scholar
  36. 36.
    Seager W, Fraser DS (2007) Comparing physical, automatic and manual map rotation for pedestrian navigation. In: Proc. SIGCHI Conf. Hum. Factors Comput. Syst. (CHI ‘07). ACM Press, pp 767–776Google Scholar
  37. 37.
    Lioli D, Komninos A (2016) Icon Design for Landmark Importance in Mobile Maps. 20th Panhellenic Conf. InformaticsGoogle Scholar
  38. 38.
    MacEachren AM (2004) How maps work: representation, visualization, and design. Guilford PressGoogle Scholar
  39. 39.
    Duncan J, Humphreys GW (1989) Visual search and stimulus similarity. Psychol Rev 96:433–458.  https://doi.org/10.1037/0033-295X.96.3.433 CrossRefGoogle Scholar
  40. 40.
    R Core Team (2014) R: a language and environment for statistical computing. R Found Stat Comput Vienna, Austria.  https://doi.org/10.1017/CBO9781107415324.004
  41. 41.
    Peirce JW (2007) PsychoPy-psychophysics software in python. J Neurosci Methods 162:8–13.  https://doi.org/10.1016/j.jneumeth.2006.11.017 CrossRefGoogle Scholar
  42. 42.
    Beeco JA, Huang W-J, Hallo JC, Norman WC, McGehee NG, McGee J, Goetcheus C (2013) GPS tracking of travel routes of wanderers and planners. Tour Geogr 15:551–573.  https://doi.org/10.1080/14616688.2012.726267 CrossRefGoogle Scholar
  43. 43.
    Lazar DJ, Feng DJH, Hochheiser DH (2010) Research methods in human-computer interaction. John Wiley & SonsGoogle Scholar
  44. 44.
    Hecorat (2017) Hecorat. http://hecorat.com/. Accessed 10 Dec 2017
  45. 45.
    The Pokémon Company (2017) Pokémon Go. https://www.pokemongo.com/en-us/. Accessed 10 Dec 2017
  46. 46.
    McGookin D, Tahiroglu K, Vaittinen T, Kytö M, Monastero B, Vasquez JC (2017) Exploring Seasonality in Mobile Cultural Heritage. Proc. SIGCHI Conf. Hum. Factors Comput. Syst. (CHI ‘17)Google Scholar

Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Computer ScienceAalto UniversityAaltoFinland

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