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Call for Papers — ACM SIGKDD Workshop on Visual Analytics and Knowledge Discovery — VAKD '09

WORKSHOP ON VISUAL ANALYTICS AND KNOWLEDGE DISCOVERY:
INTEGRATING AUTOMATED ANALYSIS WITH INTERACTIVE EXPLORATION

A full-day workshop in conjunction with
the 15th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
in Paris, France,
on 28 June 2009.

http://www.hiit.fi/vakd09

In this document:
Background | Invited Talks and Structure of the Workshop | Topics of Interest | Visual Analytics Challenge | Important Dates | Venue | Organization

Background

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 goal of this workshop is to raise the awareness of the KDD community for the importance of Visual Analytics and bring together researcher from the underlying fields to bridge the gap between them—to write a KDD research roadmap on Visual Analytics.

Invited Talks and Structure of the Workshop

The invited talks provide an overview of Visual Analytics, define its scope and challenges, and present reference Visual Analytics techniques and systems. Our invited speakers include:

The workshop will include oral and poster presentations of submitted contributions, as well as a working session that summarizes the results and maps the research landscape in Visual Analytics.

Topics of Interest

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:

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.

The length of the papers should be 10 pages or less in ACM proceedings format and they should be submitted by 20 April 2009 23:59 UTC-11. See the workshop web site for detailed submission instructions.

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. The accepted papers will be published in the ACM Digital Library before 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.

Visual Analytics Challenge

In 2008, Visual Analytics researchers were presented with a set of 4 mini-challenges concerning a fictitious, controversial socio-political movement, as a part of the IEEE Visual Analytics Science and Technology (VAST) symposium. These mini-challenges, which were designed to allow participation by a broad spectrum of researchers and tool builders, were very useful in learning about the application of Visual Analytics tools to problems similar to those working analysts face.

You are invited to work the VAST 2008 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 present examples of the VAST 2008 challenge solutions at the workshop, as a springboard to follow-on discussion.

See the workshop web site for datasets and submission instructions.

Important Dates

20 April 2009 at 23:59 UTC-11   Paper/challenge submissions
15 May 2009 Notifications of acceptance
22 May 2009 Camera ready papers
28 June 2009 Workshop in Paris, France

Venue

The workshop will be part of the 15th ACM SIGKDD Conference On Knowledge Discovery and Data Mining. See the KDD-09 web site for information about the venue and how to register to the workshop: http://www.sigkdd.org/kdd2009/

Organization

Program Committee Chairs

Fosca Giannotti & Dino Pedreschi & Salvatore Rinzivillo (University of Pisa)
Georges Grinstein (University of Massachusetts Lowell)
Otto Huisman (International Institute of Geo-Information Science and Earth Observation)
Daniel A. Keim (University of Konstanz)
Catherine Plaisant (Human-Computer Interaction Lab, University of Maryland)
Tobias Schreck (Technische Universitaet Darmstadt)
Mike Sips (Max-Planck-Institut fuer Informatik)
Dimitrios Tzovaras (Center for Research & Technology Hellas)
Anders Ynnerman & Jimmy Johansson (Linköping University)

Challenge Chairs

Mark A. Whiting & Jean Scholtz (Pacific Northwest National Laboratory)

General Chairs

Kai Puolamäki & Heikki Mannila (Helsinki Institute for Information Technology HIIT)
Alessio Bertone & Silvia Miksch (Danube University Krems)

Contact Information

Email: vakd09@hiit.fi
Web site: http://www.hiit.fi/vakd09
See the workshop web site for complete contact information.

Sponsors

VisMaster, a European FP7 Coordination Action Project focused on Visual Analytics
PASCAL2 - Pattern Analysis, Statistical Modelling and Computational Learning, a European FP7 Network of Excellence
Helsinki Institute for Information Technology HIIT
Danube University Krems, Departement of Information and Knowledge Engineering (DUK)
National Visualization and Analytics Center (NVAC)


VAKD '09 Home PageSpecial Issue | Proceedings | Program | CfP (Special Issue) | CfP (Workshop) | Challenge | Organizers | Contact

http://www.hiit.fi/vakd09/cfp.html
2009-03-24

vakd09@hiit.fi