‘George Square’ collaborative tourism system
‘George Square’ collaborative tourism system. This system uses a small, portable tablet PC to allow a mobile visitor to explore a city while sharing their voice, location, photographs and web pages with others. This tablet is connected via the Internet to other users running the same software who may either be co-present or in different parts of the city.
Described in Sharing the square: collaborative leisure in the city streets by Barry Brown, Matthew Chalmers, Marek Bell, Ian MacColl, Malcolm Hall, Paul Rudman, To appear in Proc. Euro. Conf. Computer Supported Collaborative Work (ECSCW) 2005, Paris.
[Authors] ran an extensive trial of the system in George Square in Glasgow, studying how the system could support shared visits. In this trial one visitor walked around the square looking at different attractions in the square, while a second visitor was sat indoors at a laptop computer. Both visitors could communicate through our system, talking, taking photographs and browsing the web. (...) In these trials the map was used as a resource for understanding the context of others, photographs were a resource for conversation between users and the recommendations supported talk about the different places in the square. Importantly, the system provided not only support for collaboration, but also for the sociable activities of a visit, such as talking around photographs and city features. (...) One of the main issues which hampers the deployment of such system is the difficulty in creating recommendations and marking areas. We have thus developed a GSQ editor which allows the authoring of recommendations (buildings, urls and pictures). Both location and view volume corresponding to a particular picture can be edited. To further help with marking areas, we suggest regions on the map by retrieving nearby physical features from a repository of real map features (OS Mastermap). We have extended the George Square system to apply visibility processing to prioritize recommendation that are probably visible to the user. By using information about real world buildings and features, the certainty that a particular recommendations is visible is computed. This in turn is used to provide a filtered recommendation service which has the benefit of presenting location and context sensitive information.
Why do I blog this Another location-based service devoted to tourism. However it's rather experimental than meant to be marketed. I like the annotation and marking feature as well as the visibiliy filtering capabilities.