International Symposium on Big Data Visual Analytics, Adelaide, Australien

Abbrevation

BDVA

Link

http://bdva.net/2017/

City

Adelaide

Country

Australia

Deadline Paper

2017-06-30

Start Date

2017-11-07

End Date

2017-11-10

Abstract

In the last decade, Big Data Analytics has become a major decision support factor in industry and government organisations. Visual Analytics is the enabling science for effective exploration of big data through meaningful visualisations and interactive user interfaces. Understanding the multidisciplinary nature, including user querying, powerful analytics, machine learning, visualisation, human–computer interaction, perception and cognition, is critical for Visual Analytics to be effectively deployed. The BDVA’17 Symposium will be held at the University of South Australia (UniSA) on 7–10th November 2017. BDVA’17 will host an exciting programme with internationally renowned keynote speakers, special sessions, and a day of complimentary hands–on workshops. BDVA’17 aims to * bring together leading experts from all relevant scientific domains to advance the understanding of visual analytics of complex, big, and dynamic data; * provide an exciting venue for researchers to network and establish national and international collaborations; and * provide early career scientists with an inspiring event allowing them to connect to relevant experts in the field. SCOPE The symposium will accept a range of manuscript types, including methods, systems, applications, evaluation techniques and theoretical work in Visual Analytics. The scientific scope of the symposium includes, but is not limited to: * Visual Analytics of High–dimensional and Spatio–temporal Data * Scientific and Information Visualisation * Machine Learning and Data Mining for Big Data Visual Analytics * Visual Representation and Interaction * Perception and Cognition of Visual Information * Analytical Reasoning and Sense–making on Big Data * Context–driven User Querying * Semantics–driven Visual Analytics * Evaluation Methods for Visual Analytics * Visual Analytics Algorithms and Foundations * High Performance Graphics for Visualisation * Advanced Technologies and Applications for Visual Analytics * Virtual and Augmented Reality for Visual Analytics * Art and Science for Visual Analytics * Big Data Management, Transformation, and Presentation * Visual Analytics Processes and Workflows * Simulation for Visual Analytics