Abstract
Official statistics such as demographics, environment, health, socialeconomy and education from regional territories are a rich and important source of information for many important aspects of life. Web-enabled geovisual analytics is a technique that can help illustrating comprehensive statistical data which for the eye are hard perceive or interpret. In this paper, we introduce “storytelling” means for the author to 1) select spatio-temporal and multivariate statistical data, 2) explore and discern trends and patterns, 3) orchestrate and describe metadata, 4) collaborate with colleagues to confirm and 5) finally publish essential gained insight and knowledge embedded as dynamic visualization “Vislet” in a blog or web page. The author can guide the reader in the directions of both context and discovery while at the same time follow the analyst’s way of logical reasoning. We are moving away from a clear distinction between authors and readers affecting the process through which knowledge is created and the traditional models which support editorial work. Value no longer relies solely on the content but also on the ability to access this information.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Andrienko, G., Andrienko, N.: Visual Exploration of Spatial Distribution of Temporal Behaviors. In: Proceedings of IEEE IV 2005 (2005)
Geovisual Analytics, http://geoanalytics.net/GeoVisualAnalytics08/
Geovisual Analytics tools, http://ncva.itn.liu.se/explorer/tools
OECD eXplorer (2010), http://www.oecd.org/gov/regional/statisticsindicators/explorer
Guo, D., Chen, J., MacEachren, A.M., Liao, K.: A visualization system for space-time and multivariate patterns. IEEE Visualization and Computer Graphics 12(6) (2006)
Jern, M.: Smart Documents for Web-Enabled Collaboration. In: Vince, J.A., Earnshaw, R.A. (eds.) Digital Content Creation. Springer, Heidelberg (June 2001)
Jern, M., Franzén, J.: ‘GeoAnalytics – Exploring spatio-temporal and multivariate data. In: Reviewed Proceedings, IV 2006, London. IEEE Computer Society, Los Alamitos (2006)
Jern, M., Rogstadius, J., Åström, T., Ynnerman, A.: Visual Analytics presentation tools applied in HTML Documents. In: Reviewed Proceedings, IV 2008, London. IEEE Computer Society, Los Alamitos (2008)
Jern, M., Thygesen, L., Brezzi, M.: A web-enabled Geovisual Analytics tool applied to OECD Regional Data. In: Reviewed Proceedings in Eurographics 2009, Munchen (2009)
Keel, P.: Collaborative Visual Analytics: Inferring from the Spatial Organisation and Collaborative use of information. In: VAST 2006, pp. 137–144. IEEE, Los Alamitos (2006)
MacEachren, A.M., Brewer, I., et al.: Geovisualization to mediate collaborative work: Tools to support different-place knowledge construction and decision-making. In: 20th International Cartographic Conference, Beijing, China (2001)
OECD web site, http://www.oecd.org/GOV/regionaldevelopment
Roberts, J.C.: Exploratory Visualization with Multiple Linked Views. In: Dykes, J., MacEachren, A.M., Kraak, M.-J. (eds.) Exploring Geovisualization (2004)
Robinson, A.: Re-Visualization: Interactive Visualization of the Progress of Visual Analysis. In: Workshop Proceedings, VASDS (2006)
Wohlfart, M., Hauser, H.: Story Telling for Presentation in Volume Visualization. In: EuroVis 2007 (2007)
GAV Flash class library, http://ncva.itn.liu.se/tools
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Jern, M. (2010). Explore, Collaborate and Publish Official Statistics for Measuring Regional Progress. In: Luo, Y. (eds) Cooperative Design, Visualization, and Engineering. Lecture Notes in Computer Science, vol 6240. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16066-0_29
Download citation
DOI: https://doi.org/10.1007/978-3-642-16066-0_29
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-16065-3
Online ISBN: 978-3-642-16066-0
eBook Packages: Computer ScienceComputer Science (R0)