Geography Reference
In-Depth Information
movements to be viewed and the data collected at specific locations superimposed on this
map. For example, in ethnographic studies of CYSMN, a map interface was used to select
and view video, audio and text log data for a particular location.
Rudman et al. (2005) use maps to display to the participant the CO 2 levels measured as they
walk around an urban environment. Sensors and a PDA are used to capture this CO 2 data,
with a map on the PDA providing the user with a visual representation of where they have
been and the CO 2 measured. In addition to this, photos could be taken at specific locations
and attached on the map to document the levels of traffic at interesting locations. This
information was then used to facilitate discussions and analysis about what the participants
have encountered and the levels of CO 2 pollution in different locations.
These map-based visualizations allow the user to view data based on physical locations
using accurate location positioning such as GPS. However, GPS is not always available
if we use mobile phones for data collection; therefore, a more abstract representation of
location information needs to be used. For example, Hitchers (Drozd et al. , 2006) uses
mobile phone cell IDs as a positioning service and, as such, accurate positioning on a map
is not always possible. Therefore, visualization of these cell IDs as nodes in a graph and
the transitions between cells as edges provides a way of displaying a spatial representation
of players' movements. This type of positioning is useful where GPS is not available and
analysis of players' movements and/or context is needed.
The Hitchers visualization very much relies on the context information given by players
about locations. These context labels allow the graph to become more meaningful as an
often-travelled-through cell could be a popular cafe or a major road intersection on a
player's route to work.
In the above examples we can see how location information could be visualized for the
analyst. Despite the difference in the techniques for location-tagging data, the location
information can be displayed to the analyst using the spatial nature of the data. In addition
to this location information, context information can provide additional insight into the
location data. Using Context Phone (Raento et al. , 2005), for example, as discussed in the
previous section, we can capture data about a location, such as the number of Bluetooth
connections, which could indicate how busy or densely populated the location is.
16.3.2 Visualizing context information
Context-aware systems are often associated with mobile ubiquitous computing as interac-
tions between humans and computers in these environments can be made more meaningful
by understanding the context of the participant.
Context in this case can be defined as where you are, who you are with and what resources
are nearby (Schilit et al. , 1994). Additionally, context awareness can be defined as 'any infor-
mation that can be used to characterise the situation of an entity where, an entity can be de-
fined as a person, place, or object that is considered relevant to the interaction between a user
and an application, including the user and applications themselves' (Dey and Abowd, 1999).
Both of these definitions are broad in their approach to what is context. Context can
be gathered about vision, audio, motion and location, from bio sensors and other spe-
cialised sensors (Schmidt et al. , 1999) as well as many more. Visualization of these different
combinations of variables can be a challenge and presenting multiple view visualizations of
all these variables could lead to information overload for the analyst.
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