VAKD 2010 - IEEE ICDM Workshop on Visual Analytics and Knowledge Discovery ? VAKD '10

IEEE ICDM Workshop on Visual Analytics and Knowledge Discovery ? VAKD '10
held in conjunction with
ICDM 2010: The 10th IEEE International Conference on Data Mining
December 13-17, 2010, Sydney, Australia
Workshop Description
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
Important Dates
23 July 2010 at 23:59 UTC-11 Paper/challenge submissions
20 September 2010 Notifications of acceptance
11 October 2010 Camera ready papers
13 December 2010 Workshop in Sydney, Australia
Invited Talks
The invited talks provide an overview of Visual Analytics, define its scope and challenges, and present reference Visual Analytics techniques and systems.

Visual Analytics Challenge
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
Paper Submission
Submissions have to be 10 pages or less in IEEE 2-column format submitted electronically via Easy 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.

Proceedings
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.

Organizers
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
Program Committee (not complete)
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, Penn State, USA
Joern Schneidewind, Telefonica-o2, Germany
Tobias Schreck, Technische Universitaet Darmstadt, Germany
Sponsors
VisMaster, a European FP7 Coordination Action Project focused on Visual Analytics
National Visualization and Analytics Center (NVAC)
Department of Homeland Security (DHS)
European Archive