Abstract. Here we sketch the rudiments of what constitutes a smart city which we define as a city in which ICT is merged with traditional infrastructures, coordinated and integrated using new digital technologies. We first sketch our vision defining seven goals which concern: developing a new understanding of urban problems; effective and feasible ways to coordinate urban technologies; models and methods for using urban data across spatial and temporal scales; developing new technologies for communication and dissemination; developing new forms of urban governance and organisation; defining critical problems relating to cities, transport, and energy; and identifying risk, uncertainty, and hazards in the smart city. To this, we add six research challenges: to relate the infrastructure of smart cities to their operational functioning and planning through management, control and optimisation; to explore the notion of the city as a laboratory for innovation; to provide portfolios of urban simulation which inform future designs; to develop technologies that ensure equity, fairness and realise a better quality of city life; to develop technologies that ensure informed participation and create shared knowledge for democratic city governance; and to ensure greater and more effective mobility and access to opportunities for a

We present an approach to the process of constructing knowledge through structured exploration of large spatiotemporal data sets. First, we introduce our problem context and de® ne both Geographic Visualization (GVis) and Knowledge Discovery in Databases (KDD), the source domains for methods being integrated. Next, we review and compare recent GVis and KDD developments and consider the potential for their integration, emphasizing that an iterative process with user interaction is a central focus for uncovering interest and meaningful patterns through each. We then introduce an approach to design of an integrated GVis-KDD environment directed to exploration and discovery in the context of spatiotemporal environmental data. The approach emphasizes a matching of GVis and KDD meta-operations. Following description of the GVis and KDD methods that are linked in our prototype system, we present a demonstration of the prototype applied to a typical spatiotemporal dataset. We conclude by outlining, brie¯y, research goals directed toward more complete integration of GVis and KDD methods and their connection to temporal GIS.

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No abstract

This issue of Information Visualization showcases research activity involving and contributing to the visual analysis of dynamism, movement and change in phenomena that have a spatial element.The work presented here represents a selection of the contributions made to a workshop coordinated by the International Cartographic Association (ICA) Commission on Geovisualization and the Association of Geographic Information Laboratories in Europe (AGILE) on the Geovisualization of Dynamics, Movement and Change. Theoretical and methodological approaches for exploring and analyzing large datasets with spatial and temporal components were presented, discussed and developed at the meeting in Girona, Catalunya which was held on 5 th May 2008 one day before AGILE's 11th International Conference on Geographic Information Science.The high level of interest raised by the open call for contributions and the ultimate participation of more than 40 scientists suggests that this theme is timely and of relevance to many researchers and research groups. It would also seem to indicate that spatiotemporal data pose plenty of interesting and unsolved research problems. The workshop, and the work subsequently reported here suggest that many of these are complex and can benefit from the application of cross-disciplinary approaches. Cross-disciplinarity has been reflected not only in the contents of the submissions, but also in the composition of the workshop delegates, which included scientists from a variety of nations with backgrounds in geography, geographic information science, information visualization, data mining and other cognate disciplines. We reflect upon some of these trends in this introduction to the papers.Integration of approaches from multiple disciplines is a characteristic feature of geovisualization -a research domain addressing the visual exploration, analysis, synthesis, and presentation of geographic data, information, and knowledge (Dykes et al. 2005). The ICA Commission on Geovisualization works to develop, promote and communicate advances in this multidisciplinary domain -http://geoanalytics.net/ica. One way of so doing is to attract researchers with various disciplinary backgrounds to themed workshops that showcase current multidisciplinary approaches whilst allowing participants to learn about relevant theories and methods existing in related fields. They also create new opportunities for considering problems from different perspectives, and for starting new cross-disciplinary collaborations.