information visualization

W. Aigner, “Interactive Visualization and Data Analysis: Visual Analytics With a Focus on Time”. 2013.
P. Bodesinsky, Federico, P., and Miksch, S., “Visual Analysis of Compliance with Clinical Guidelines”, in Proceedings of the 13th International Conference on Knowledge Management and Knowledge Technologies (i-KNOW), 2013, pp. 12:1–12:8.
A. Rind, Lammarsch, T., Aigner, W., Alsallakh, B., and Miksch, S., “TimeBench: A Data Model and Software Library for Visual Analytics of Time-Oriented Data”, IEEE Transactions on Visualization and Computer Graphics, Special Issue "VIS 2013", vol. 19, no. 12, pp. 2247-2256, 2013.
W. Aigner, “Current Work Practice and Users' Perspectives on Visualization and Interactivity in Business Intelligence”, in Proceedings of 17th International Conference on Information Visualisation (IV13), 2013, pp. 299-306.
B. Fisher and Miksch, S., “Guest Editors' Introduction to the Vast 2010 Special Issue-Special Issue of best papers of Visual Aanlytics Science and Technology (VAST) 2010”, Information Visualization, vol. 11, no. 3, pp. 188–189, 2012.
IEEE Conference on Visual Analytics Science and Technology 2010 (VAST 2010). Danvers, MA: IEEE Computer Society Press, 2010, p. 292.
A. M. MacEachren and Miksch, S., “Guest Editors' Introduction: Special Section on the IEEE Conference on Visual Analytics Science and Technology (VAST)”, IEEE Transactions on Visualization and Computer Graphics, vol. 18, pp. 660–661, 2012.
A. Rind et al., “Visual Exploration of Time-oriented Patient Data for Chronic Diseases: Design Study and Evaluation”, in Proceedings of USAB 2011: Information Quality in e-Health, 2011, pp. 301–320.
P. Federico, Aigner, W., Miksch, S., Windhager, F., and Zenk, L., “A Visual Analytics Approach to Dynamic Social Networks”, in Proceedings of the 11th International Conference on Knowledge Management and Knowledge Technologies (i-KNOW), Special Track on Theory and Applications of Visual Analytics (TAVA), 2011, pp. 47:1–47:8.
A. Bertone, “A Matter of Time: how to visually analyze multivariate (and multidimensional) data, irregularly sampled and having multiple granularities”, in Doctoral Consortium in AIME 07 Conference, 2007, pp. 9–16.