The broad distribution of modern technological achievements such as GPS tracking and mobile phones in society has brought rapidly increasing datasets of spatio-temporal movement data. These accumulated movement data represents an challenging object for study with the aim to extract information and analyse the complex movement patterns (COST - MOVE, 2009; Keim et al., 2008). This results in the development of new visual analytical and exploratory tools, while existing solutions receive new attention (Andrienko et al., 2007). Among the last the Space Time Cube (STC) can be grouped. It has the ability to provide information about spatial and temporal relationships. The original idea of STC was introduced by Hägerstrand (1970). It represents an elegant framework to study spatio-temporal characteristics of human activity (Kraak and Koussoulakou, 2005). The vertical dimension of cube represents time (t), while horizontal axes represent space (x, y). Basic elements represented in the cube are the Space-time Path (STP), Stations, and the Space Time Prism (STP). The STP represents the continuous activities of movements undertaken in space and time displayed as trajectory. It has been studied in transportation (Miller, 2003), gender studies (Kwan, 1999) among others. Stations are locations of no-movement and are the vertical lines in a path. They can also be used separately of the paths as done by Gatalski (2004), while analyzing earthquake information. Or by Kraak & Madzudzo (2007) to analyze the Black Death locations in 14th century in Europe. The STP, representing a reachable space by individual in an available time and is utilized in the study of space-time accessibility. It has been used by Neutens (2010), and as taxels (volume of cells) by Forer and Huisman (1998), with the aim to aggregate the similar socioeconomic groups of individuals. However, despite all those experiments it is not known if the STC really delivers what is potentially has to offer, especially when it come to represent large volumes of data. Limited usability research has been done, and only for specific cases (Kristensson et al., 2009). Also the environment where the STC is used is constantly changing. Today it would be just a one of the potential elements in a geovisual analytics environment. To find out how the STC behaves a research project has been set up that will consider three use case scenarios in varying complexity. The scenarios include a relatively simple movement data set, a complex multivariate movement data and a very large amount of movement data for each of the scenarios. Moreover special attention will be given to the cartographic design. However, user requirements are likely to influence the visualization strategies and demand for specific functionality. Usability testing should provide answers to questions such as; how does STC work? What are its limitations? Does the user understand the applications in STC? In this particular paper we will concentrate on the first case scenario, a relatively simple set of movement data with multiple paths. In addition, the developed working environment of the STC will be presented.
|Publication date||26 Aug 2010|
|Publication status||Published - 26 Aug 2010|