2011-05-16: CFP: Special Issue of the journal Data Mining and Knowledge Discovery on Intelligent Interactive Data Visualization

Special Issue of the Journal of Data Mining and Knowledge Discovery on Intelligent Interactive Data Visualization, published by Springer

Guest Editors: Barbara Hammer, Daniel Keim, Neil Lawrence, Guy Lebanon

The increasing amount and complexity of electronic data poses problems for domain experts or users who analyze that data. They cannot rely on fully automatic techniques for data analysis and visualization, because effective modeling requires an iterative interaction between computerized processing and human analysis. Such a human-in-the-loop approach enables domain experts or users to interactively refine their hypotheses and modeling assumptions and arrive at conclusions that are impossible for the computer to reach on its own. Intelligent data visualization and its interaction with traditional machine learning serve a central role in this process. The aim of the exciting new discipline of visual analytics is to develop intelligent interactive visualizations of data. Visual analytics intersects machine learning, intelligent systems, pattern analysis, visualization, computer graphics, and human computer interaction. This special issue is intended to encourage approaches of machine learning and intelligent systems to contribute to challenges in the emerging area of visual analytic.

Topics covered, but not limited to, include:

• Dimensionality reduction and visualization of streaming data, non iid data, structured, or heterogeneous data
• Evaluation measures and canonical datasets for data visualization
• Practical case studies demonstrating successes and failures in modern domain areas
• Integration of domain knowledge into data visualization
• Iterative refinement of data visualization based on user feedback
• Theoretical issues concerning data visualization
• Computational issues including developing tractable approximations when needed
• Connections and reductions between visualization and other machine learning tasks, such as classification, clustering, regression, density estimation

Manuscripts should be submitted to http://DAMI.edmgr.com until September 1st, 2011.

Important dates

• Manuscript submission deadline: September 1, 2011
• Notification of acceptance: November 1, 2011
• Revised manuscript submission: February 1, 2012
• Notification of acceptance for revised: April 1, 2012
• Final papers due: June 1, 2012

by Daniel Keim