Abstract -Exploratory visual analysis is useful for the preliminary investigation of large structured, multifaceted spatio-temporal datasets. This process requires the selection and aggregation of records by time, space and attribute, the ability to transform data and the flexibility to apply appropriate visual encodings and interactions. We propose an approach inspired by geographical 'mashups' in which freely-available functionality and data are loosely but flexibly combined using de facto exchange standards. Our case study combines MySQL, PHP and the LandSerf GIS to allow Google Earth to be used for visual synthesis and interaction with encodings described in KML. This approach is applied to the exploration of a log of 1.42 million requests made of a mobile directory service. Novel combinations of interaction and visual encoding are developed including spatial 'tag clouds', 'tag maps', 'data dials' and multi-scale density surfaces. Four aspects of the approach are informally evaluated: the visual encodings employed, their success in the visual exploration of the dataset, the specific tools used and the 'mashup' approach. Preliminary findings will be beneficial to others considering using mashups for visualization. The specific techniques developed may be more widely applied to offer insights into the structure of multifarious spatio-temporal data of the type explored here. Index Terms -Large dataset visualization, text and document visualization, multiresolution visualization, geographic visualization, applications of infovis. Extracting structure, meaning and insight from large, multifaceted, spatio-temporal datasets is a challenging task and such data are consequently underused in many application domains [1] . This paper considers how the increasingly used 'mashup' approach to software and data integration can be applied to exploratory visualisation in order to address this underuse. In doing so, wider issues for the use of mashups in visualisation are identified. Exploratory visual analysis that proceeds in an iterative fashion can be a highly effective means of preliminary investigation [2, 3] . Such analyses require the means to select, inspect and modify visual encodings, with data transformed, filtered, sampled and aggregated according to time-, space-and attribute-based criteria. As the exploration proceeds, flexibility is needed to generate new samples, derivatives (such as alternate spatial aggregations), filterings and visual encodings in response to the insights and informal hypothesis gained and to integrate these with ancillary data. This process can be likened to Shneiderman's [4] "visual information-seeking mantra: overview first, zoom and filter, then details-on-demand". Off-the-shelf geographic information systems (GIS) provide some of the functionality, particularly for spatial processing, but less flexibility for geovisualization. The alternative of developing tools from scratch with the required flexibility is difficult, time-consuming and requires skills not possessed by many engaged in geovisualization. Development effort may hinder progress and be too slow to allow iteration to be of sufficient benefit [5] . For this reason, toolkits have been developed that allow different interactive visualization components to be linked together using scripting or programming languages; e.g. GeoVISTA Studio [6], InfoVis Toolkit [7] , and Improvise [8] . These frameworks can be used to build powerful visualization applications from specialist components. We propose an alternative approach for the exploration of data that has considerable potential. It is inspired by the geographical mashup, which takes a set of open and freely-available resources, and combines them using de facto standards often based on XML. The use of general purpose scripting offers flexibility in interactive visual encoding specification and the filtering and processing of data according to spatial, temporal and attribute criteria, potential for rapid prototyping, and opportunities for distribution so that others can be invited to explore data and integrate findings with other data and software. We demonstrate this approach with a geovisualization mashup case study in which we use Google Earth [9] for interactive visual synthesis of encodings generated using a combination of MySQL [10] (for data storage and querying to select and aggregate), PHP (for linking the database and the server and generating output) and LandSerf (for surface processing, calculating spatial derivatives and output). KML [11] is used to describe visual encodings and define interactions. This combination allows us to store, query, process and produce abstract graphics. Google Earth is used as a means of interactively visually analysing and synthesising data, through its spatial and temporal navigation tools, its access to wider contextual data, its ability to stream data from servers in response to user interaction and its embedded HTML browser. We use this combination of tools to visually explore a mobile directory service log file containing 1.42 million records with spatial, temporal and attribute components. We demonstrate the flexibility of the approach by designing a set of interactive abstract graphics: 'tag clouds', 'tag maps', 'data dials' and 'geo-mipmaps' which visually synthesise data and provide interactive means of filtering and aggregating by space, scale, time and attributes. These are used in conjunction with other ancillary data to explore the dataset. The approach is informally evaluated at several levels. Firstly, we reflect on the success of the specific interactive visualizations which both synthesise data at multiple spatial, temporal and attribute aggregations, and act as bases for filtering of the data. Secondly, we focus on characteristics of our data that have been revealed and warrant further investigation. Thirdly, we contemplate the specific tools and languages we have used in the mashup. Finally, we consider the geographical mashup approach and discuss the value of its use for the initial stages of the exploratory process as well as the information visualization development process as a whole. We argue Jo Wood (jwo@soi.city.ac.uk), Jason Dykes (jad7@soi.city.ac.uk), and Aidan Slingsby (a.slingsby@city.ac.uk) are based at the giCentre,
In a paper published relatively early, Wood et al. REF describe the use of Google Earth for visualizing a large mobile directory service log file with spatial, temporal and attribute components as tags on top of the geography.
Interactive Visual Exploration of a Large Spatio-temporal Dataset: Reflections on a Geovisualization Mashup.
IEEE Transactions on Visualization and Computer Graphics
IEEE Transactions on Visualization and Computer Graphics
Computer Science Medicine