held in conjunction with
ICDM 2010: The 10th IEEE International Conference on Data Mining
December 14-17, 2010, Sydney, Australia

Session 1: Welcome and Invited Talk
9:00 AM	Welcome
9:10 AM	Invited Talk: Peter Eades "Its hard to draw a graph"
Session 2: Oral Presentations
10:30 AM	Christin Seifert and Michael Granitzer, User-based active learning
10:55 AM	Kai Puolamaki, Panagiotis Papapetrou, and Jefrey Lijffijt, Visually Controllable Data Mining Methods
11:20 AM	Scott Spangler, Ying Chen, Jeffrey Kreulen, Stephen Boyer, Thomas Griffin, Alfredo Alba, Linda Kato, Ana Lelescu, and Su Yan, SIMPLE: Interactive Analytics on Patent Data
11:45 AM	Martin Hahmann, Dirk Habich, and Wolfgang Lehner, Evolving Ensemble-Clustering to a Feedback-Driven Process
Lunch Break
Session 3: Invited Talk and Challenge Panel
1:30 PM	Invited Talk: Bart Goethals "Visual Pattern Mining"
2:20 PM	Hanisha Veeramachaneni, Soujanya Vadapalli, and Kamalakar Karlapalem, BODY - Buckets Of Disease sYmptoms for Disease Outbreak Analysis
2:45 PM	Rafael Guimarães, Nikolas Carneiro, Bianchi Meiguins, and Aruanda Meiguins, Analysing large-scale, time-oriented datasets with PRISMA
3:10 PM	Challenge Panel Preferably folks who has seen the real world
Session 4: Oral Presentation and Collaboration Panel
4:00 PM	Martin Amèlie, Monique Noirhomme-Fraiture, Quang Vinh Nguyen, and Simeon Simoff, A Visual Analytics Tool for Analysing Microarray Data
4:25 PM	Eniko Szekely, Eric Bruno, and Stephane Marchand-Maillet, High-dimensional multimodal distribution embedding
4:50 PM	Panel Keynote: Joseph Kielman "Research Directions and Collaborations in Visual Analytics"
Session 5: Collaboration Panel Research Directions in the interplay of Knowledge Discovery and Interactive Visualization
5:15 PM
Session 6: Closing Session
5:55 PM	Wrap-Up
5:55 PM	End of Workshop
7.30 PM	Dinner: Future of VAKD

Visual Analytics is a relatively new multidisciplinary field that combines various research areas including knowledge discovery, data analysis, visualization, human-computer interaction, data management, geo-spatial and temporal data processing and statistics. The goal of Visual Analytics is to derive insight from massive, dynamic, ambiguous, and often conflicting data; detect the expected and discover the unexpected; provide timely, defensible, and understandable assessments; and communicate the assessment effectively for action. An integration of the increasing processing power of computers with the efficient pattern recognition abilities and domain knowledge of human analysts is a challenging and promising road in dealing with large amounts of complex data. It will be also a major driving force for solutions for information overload in many research and commercial areas.

The objective of this workshop is to bring together researchers and practitioners that are developing and applying the state-of-the-art in visual analytics; to provide a forum for presentation and discussion of the newest both mature and greenhouse ideas, research and developments in visual analytics and supporting disciplines, and to identify the short- and long-term research directions in the field and preferences of the potential end users.

We solicit papers that will introduce new research results, present forward-looking positional statements, or define relevant research challenges.

Topics of interest include, but are not limited to:

• Visual analytics process models
• Complexity, efficiency and scalability of visual analytics techniques
• Incorporation of domain knowledge in visual analytics
• Algorithmic animation methods for visual data mining
• Cognitive aspects of information visualization in data mining
• Multi-modal technologies for visual analytics
• Interactivity in visual analytics
• Visual languages in visual analytics
• Visual representation of discovered knowledge
• Efficient data processing algorithms for visual computing
• Metrics and evaluation methods for visual analytics
• Generic visualisation architectures
• Methods for visualising semantic content
• Visual analytics of integrated data sets, including text, graph and digital media data
• Collaborative visual analytics, including high-end virtual environments
• Visual data abstraction
• Visual analysis of large graphs and networks
• Visual exploration of data warehouses
• Integrated visualisation of raw data and analysis results
• Perceptual and cognitive factors visual analytics
• Interaction paradigms and human factors in visual analytics

9 August	Paper/challenge submissions
20 September 2010	Notifications of acceptance
11 October 2010	Camera ready papers
14 December 2010	Workshop in Sydney, Australia

You are invited to work the VAST 2008-2010 challenges, and use those datasets, to illustrate your KDD/VA research. A distinct advantage to you in using these datasets is that we will be able to compare and contrast approaches taken by the Visual Analytics community with yours and examine the possibilities for synergies between the two communities. We will provide additional guidance into the adjusted tasks to make the challenge interesting to the KDD community.

We will present examples of the VAST 2008, 2009, and 2010 challenge solutions at the workshop, as a springboard to follow-on discussion.

• KDD-09 specific instructions for submissions
• VAST 2008 challenge information
• Datasets
• IEEE VAST 2009 Challenge
• IEEE VAST 2010 Challenge

Submissions have to be 10 pages or less in IEEE 2-column format submitted electronically via Cyber Chair.

We strongly encourage (but do not strictly require) all contributors to use at least some of the challenge tasks described below to demonstrate the methods and concepts proposed in the contributions. This will support the discussion by making the position papers more concrete by providing a common problem for all, as well as serve as uniform benchmark data set for the workshop submissions.

In addition to original contributions we will consider papers based on recently published outstanding works, given that the original papers are adequately cited and the status is clearly stated in the contribution.

CRC versions of the papers can be submitted via http://www.ieeeconfpublishing.org/cpir/AuthorKit.asp?Community=CPS&Facility=CPS_Nov&ERoom=ICDM-W+2010

All submitted papers will be reviewed for quality and originality by the Program Committee. Based on this review, the papers will be accepted for oral and/or poster presentations, or rejected. The review process will not be double-blind (i.e., the reviewers can see your identity, you do not have to anonymize your paper).

Papers will be selected by the program committee through a peer-review process and they will be presented in oral and/or poster sessions in the workshop. Selected papers will be invited to be published in a special journal issue or proceedings after the workshop, along with the conclusions of the workshop.

Simeon Simoff
Professor of Information Technology, Head of School
School of Computing and Mathematics,
University of Western Sydney, NSW 1797
Australia
s.simoff [at] uws.edu.au

Pak Chung Wong
Chief scientist and project manager
Pacific Northwest National Laboratory PNNL
P.O. Box 999, J4-32
Richland, WA 99352
USA
pak.wong [at] pnl.gov

Mike Sips
Research Scientist
GFZ German Research Centre for Geosciences
Section 1.3, Earth System Modelling
Telegrafenberg, A20 303
14473 Potsdam
Germany
sips [at] gfz-potsdam.de

Arturas Mazeika
Research Scientist
Max-Planck-Institut Informatik
Department 5: Databases and Information Systems
Campus E 1 4
66123 Saarbruecken
Germany
amazeika [at] mpi-inf.mpg.de

• Gennady Andrienko, Fraunhofer Institute IAIS, Germany
• Alessio Bertone, Donau-Universitaet Krems, Austria
• Michael Boehlen, University of Zuerich, Switzerland
• Urska Cvek, LSU Shreveport, USA
• William S. Cleveland, Purdue Univerity, USA
• Joachim Giesen, Friedrich-Schiller-Universitaet Jena, Germany
• Maolin Huang, University of Technology, Australia
• Otto Huisman, ITC, University of Twente, The Netherlands
• Jimmy Johansson, Linkoeping University, Sweden
• Anne Kao, The Boeing Company, USA
• Paul Kennedy, University of Technology, Australia
• Quang Vinh Nguyen, University of Western Sydney, Australia
• Thomas Nocke, Potsdam Institute for Climate Impact Research, Germany
• Panagiotis Papapetrou, Aalto University, Finland
• Kai Puolamaki, Aalto University, Finland
• Anthony Robinson, The Pennsylvania State University, USA
• Joern Schneidewind, Telefonica-o2, Germany
• Tobias Schreck, Technische Universitaet Darmstadt, Germany
• Peter Bak, University of Konstanz, Germany
• Chaomei Chen, Drexel University, USA
• Silvia Miksch, Donau-Universitaet Krems, Austria
• William Pike, Pacific Northwest National Laboratory, USA
• Catherine Plaisant, University of Maryland Institute for Advanced Computer Studies, USA
• Jean Scholtz, Pacific Northwest National Laboratory, USA
• Christian Tominski, University of Rostock, Germany
• Chris Weaver, University of Oklahoma, USA
• Mark Whiting, Pacific Northwest National Laboratory, USA
• Anders Ynnerman, Linköpings Universitet, Sweden

VisMaster, a European FP7 Coordination Action Project focused on Visual Analytics