GeoVA(t) – Geospatial visual analytics: focus on time

The focus of this special issue is TIME in the specific context of geospatial visual analytics. The work presented here originates from a workshop on GeoVA(t) organised in May 2010 at the AGILE conference by the Commission on GeoVisualisation of the International Cartographic Association (http:// geoanalytics.net). Since the mid-1990s the commission has regularly published journal special issues and edited books that reflect the state of the art and the developing research agenda in geovisualisation – a form of interactive map use focussing on the exploratory analysis of spatial data (MacEachren 1994, MacEachren and Kraak 1997, 2001, Dykes et al. 2005, Andrienko et al. 2007, Fabrikant and Lobben 2009). But it is not just spatial data that benefits from interactive analysis. The rapid growth in the volumes of various types of data that now require visual representation and analysis and the increasing complexity of the data and analytical problems in many areas has resulted in the emergence of a new scientific discipline – Visual Analytics (Thomas and Cook 2005, Keim et al. 2008). The key objective of visual analytics is effective problem solving – by combining the strengths of human and computational data processing. This is achieved through highly responsive interfaces to systems that integrate interactive visualisation with efficient computation and database processing. These aims are in line with many of the research issues identified and addressed by the commission in the geospatial domains through ‘Research Challenges in Geovisualisation’ collectively documented a decade ago (MacEachren and Kraak 2001) focussed specifically on Novel Graphical Representation (Fairbairn et al. 2001), Cognitive, Usability and Interface Issues (Cartwright et al. 2001, Slocum et al. 2001) and the Integration of Geographic Visualisation with Knowledge Discovery in Databases and Geocomputation (Gahegan et al. 2001). The geovisualisation community continues to work in these areas contributing to the new broader discipline by sharing knowledge and experience and considering the specifics and complexities of space and time and proposing appropriate solutions whilst benefitting from more generic approaches and alternative perspectives on visualisation (Andrienko et al. 2008). Indeed spatial scientists participating in the European Coordination Action VisMaster (http://www.vismaster.eu) recently worked together to define a roadmap for future visual analytics research: ‘Space, Time and Visual Analytics’ (Andrienko et al. 2010). This article draws attention to the core and unique characteristics of phenomena in space and time and the data and methods that we use to understand them in the context of visual analytics. In a way, this article shows how far things have moved since the early days of the ICA Commission on Geovisualisation.