VAST 2018 : IEEE Symposium on Visual Analytics Science and Technology

  in Conferences   Posted on February 18, 2018

Conference Information

Submission Deadline Wednesday 21 Mar 2018
Conference & Submission Link http://ieeevis.org/year/2018/info/call-participation/vast-paper-types
Conference Dates Oct 21, 2018 - Oct 26, 2018
Conference Address Berlin, Germany
Proceedings indexed by
Conference Organizers : ( Deadline extended ? Click here to edit )

Conference Ranking & Metrics (This is a TOP Conference)

Google Scholar H5-index: 19
CORE 2017 Rating:
Guide2Research Overall Ranking: 256
Category Rankings
Image Processing & Computer Vision 32
Graphics & Computer-Aided Design 20
Human Computer Interaction 37

Conference Call for Papers

Visual analytics is the science of analytical reasoning supported by highly interactive visual interfaces. People use visual analytics tools and techniques in all aspects of science, engineering, business, and government to synthesize information into knowledge; derive insight from massive, dynamic, and often conflicting data; detect the expected and discover the unexpected; provide timely, defensible, and understandable assessments; and communicate assessments effectively for action. The issues stimulating this body of research provide a grand challenge in science: turning information overload into a significant opportunity. Visual analytics requires interdisciplinary science, going beyond traditional scientific and information visualization to include statistics, mathematics, knowledge representation, management and discovery technologies, cognitive and perceptual sciences, decision sciences, and more. Your submission should help develop and/or apply visual analytics, clearly showing an interdisciplinary approach.

From its outset, IEEE VAST has always given great emphasis to applications of visual analytics. While VAST 2018 seeks submissions in all areas of visual analytics, it particularly welcomes papers that make advances towards understanding or solving real world problems, or that impact a particular application in a significant way. A strong application paper, for which technique novelty is not essential, typically features one of the following qualities: namely high or broad impact, novel application, innovative technical adaptation or integration, or insightful experience or evaluation. For further discussion of application papers, see the VAST paper types below.
Topics

Suggested topics for papers include, but are not limited to:

Visual representations and interaction techniques including the principles for depicting information, new visual paradigms, statistical graphics, geospatial visualizations, the science of interaction, and approaches for generating visual analytic visualization and interactions.
Data management and knowledge representation including scalable data representations for high volume and stream data, statistical and semantic signatures, and synthesis of information from diverse data sources.
Mathematical foundations and algorithms for data transformations to allow interactive visual analysis.
Analytical reasoning including the human analytic discourse, knowledge discovery methods, perception and cognition, and collaborative visual analytics.
Presentation, production, and dissemination methods including methods and tools for capturing the analytics process, methods for elicitation of stakeholder constraints, priorities & processes for incorporation in analysis, and storytelling for specific and varying audiences.
Applications of visual analysis techniques, including but not limited to applications in science, engineering, humanities, business, public safety, commerce, and logistics as far as they contribute to visual analytics are of particular interest.
Evaluation methods, visual ethical analysis such as privacy, security, & regulatory compliance, interoperability, and technology practice & experience.
Discourse visualization and visual representations of the reasoning process.
Algorithms and technologies which are fundamental for visual analytics, including user and device adaptivity, web interfaces and mobile or other novel devices.

Please note that topics primarily involving spatial data (such as scalar, vector and tensor fields) might be a better match for SciVis: the IEEE Conference on Scientific Visualization at IEEE VIS. Similarly, topics which clearly focus on information visualization, e.g., graphical representation of abstract data to aid cognition, might be a better match for InfoVis: the IEEE InfoVis Conference, also at IEEE VIS. Papers chairs reserve the right to move papers between conferences based on its topic and perceived fit.
Paper Types

VAST has two tracks, TVCG and Conference-only tracks, which correspond to different levels of originality, rigor, and significance. In general, VAST papers should be written, submitted and reviewed in the same way as papers at the other two VIS conferences (i.e., InfoVis and SciVis), following the detailed submission guidelines. However, with the rapid development of the science, technology and application of visual analytics, it is sensible to adjust our understanding of VAST publications from time to time. We provide the following clarifications about paper types for VAST 2018, beyond the discussion of the five paper types in the shared guidelines.

In visual analytics, concepts, theories, algorithms, techniques, designs, systems, empirical studies and applications normally create a context where analysis, visualization and interaction are integrated to optimize the combination of human and machine capabilities. It is this context that differentiates VAST from other conferences in VIS, while data involved can be spatial or non-spatial, techniques can be human-centric or machine-centric, and the application domain can be almost any academic discipline, industry, business sector, or governmental operation. Within such a context, an individual VAST paper may give a strong focus on an aspect where novel contributions reside, or place its emphasis on the integration of different aspects.

VAST papers typically fall into one of these six categories:

Theory and Model
Technique and Algorithm
Design Study
Empirical Study (referred to as the Evaluation type in in the shared guidelines)
Application (as a separate category from the Design Study type in the shared guidelines)
System

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