Visualizing Data Gathered by Mobile Phones - Geographic Visualization: Concepts, Tools and Applications - page 311

However, often we are only capturing a small sub set of these variables. For example,
Cyberguide (Long et al. , 1996) only captures location and orientation context information.
Even though this context information is, as the authors state, limited, it can still elicit
meaningful information about the user's context that can be actively used.
Similarly, ActiveMap (McCarthy and Meidel, 1999) displays location information to sup-
port informal meetings between colleagues within a work environment. In this example the
context information is not only the location but also the movement of different users, the
'freshness' of this information and groups of users at specific locations.
In the two examples above location is a major part of context awareness. However, lo-
cation is not the only measurable context information we can gather, especially using mo-
bile phones. As we have discussed, ContextPhone (Raento et al. , 2005) and other context-
gathering software/hardware such as SenSay (Siewiorek et al. , 2003) allow a rich picture
to be built up about a participant's movements, actions, environment and awareness. An-
other important aspect of context information is the notion of time and the history of a
participant's context over time and how this changes.
16.3.3 Using time to provide additional insight
Time, as mentioned above, is an important part of visualizing the participants' context.
Temporal visualizations allow the analyst to replay or view interesting events over time.
Additionally, time visualizations can allow the analyst to view a snap shot or global pic-
ture of this information. For example, PeopleGarden (Xiong and Donath, 1999) visualizes
user interaction on messages boards or chat rooms to allow new users to quickly gain an
understanding of the other users' activities.
In the above sections we have explored the types of data we can capture using mobile
phones as well as the types of visualizations that we could use to visualize this data. In the
following section we shall look at two case studies where mobile phones have been used to
capture data. These case studies focus on pervasive games from the Mixed Reality Laboratory
(MRL) at the University of Nottingham, where text data from a mobile pervasive game was
captured and location-tagged using cell ID data. This data was built up over the duration
of the game and context information is gathered by inspecting the text gathered from the
game play. Visualizations of this data were implemented to explore patterns of game play
for future use in our exploration of pervasive games at the MRL.
16.4 Case studies
16.4.1 Hitchers
Hitchers (Drozd et al. , 2006) is a game for mobile phones that exploits cellular positioning
to support location-based play. Players create digital hitch-hikers, and give them names,
destinations and questions to ask other players which they drop into their current phone
cell. By searching their current cell, players are able to view a list of hitchers currently in
that cell and can pick them up, answer their questions, carry them to new locations and
drop them again, providing location-labels as hints to where they can be found. In this way,