mSpace Mobile: Exploring Support for Mobile Tasks

Abstract

In the following paper we present a formative study comparing two Web application interfaces, mSpace Mobile and Google Local in supporting Web-based location discovery tasks on mobile devices while stationary and while on the move. While mSpace Mobile performed well in both stationary and mobile conditions, performance in Google Local dropped significantly in the mobile condition. We postulate that mSpace Mobile performed better because it breaks the paradigm of the page for delivering Web content, thereby enabling new and more powerful interfaces to be used to support mobility.

Was it worth the hassle?

“…Similarly, Lumsden et al [45] simulate a city street using a surround sound system in the lab to deliver recorded city street noise, and projections on the floor to create virtual obstacles that the user should try to avoid when walking around the lab. Such simulation of mobility is also found in other lab studies, for example in the work by Wilson et al [62] and Maly et al [48] where test subjects were asked to walk and navigate a track with a number of obstacles, or in Banard et al [6] where they are asked to walk on a treadmill. An example of including the presence and activity of other people in a lab study is found in the work of Leitner et al [44] who simulate a traffic accident to users of an emergency response system.…”

Semantic reasoning on mobile devices: Do Androids dream of efficient reasoners?

“…For instance, the SHERLOCK system [4] uses a semantic reasoner and background knowledge about means of transport to infer that both a cab and a tram are interesting for a certain mobile user, given the information obtained from sensors on his/her device such as the location and time. Other location-based semantic applications that could benefit from semantic reasoners are DBpedia Mobile [5] and mSpace Mobile [6].…”

Ubiquitous Semantic Applications

“…Ultimately, users are empowered to fight the increasing information overload and gain better access to relevant documents and answers related to their information needs. • For information presentation, semantically enriched documents can be used to create more sophisticated ways of flexibly visualizing information, such as geospatial maps as described in Viana, Filho, Gensel, Oliver, and Martin (2007), Braun, Scherp, and Staab (2010), Wilson, Russell, Smith, Owens, and M. C. Schraefel (2005). • For information integration, semantically enriched documents can be used to provide unified views on heterogeneous data stored in different applications by creating composite applications such as semantic mashups, like ones presented in Wilson et al (2005), and Ermilov et al (2011).…”

“…• For information presentation, semantically enriched documents can be used to create more sophisticated ways of flexibly visualizing information, such as geospatial maps as described in Viana, Filho, Gensel, Oliver, and Martin (2007), Braun, Scherp, and Staab (2010), Wilson, Russell, Smith, Owens, and M. C. Schraefel (2005). • For information integration, semantically enriched documents can be used to provide unified views on heterogeneous data stored in different applications by creating composite applications such as semantic mashups, like ones presented in Wilson et al (2005), and Ermilov et al (2011). • To realize personalization, semantic documents provide customized and contextspecific information which better fits user needs and will result in delivering customized applications such as personalized semantic portals (e.g.…”