Big Data Visual Analytics

NII Shonan Meeting:

@ Shonan Village Center, November 8-11, 2015

NII Shonan Meeting Report (ISSN 2186-7437):No.2015-17

Organizers

  • Seok-Hee Hong, The University of Sydney, Australia
  • Koji Koyamada, Kyoto University, Japan
  • Kwan-Liu Ma, UC Davis, USA

Overview 064 Group Photo

Description of the meeting

Summary:
High-throughput technologies have produced Big Data in many application domains in Science and Engineering including Biomedical Engineering, Genomics, Software Systems, Computer Networks, Finance, e-commerce, Cyber intelligence, and Homeland Security. The ability to analyze such Big Data for knowledge discovery and decision-making is critical to scientific advancement, business success, clinical treatments, cyber and national security, and disaster management.

Visual Analytics is the science of analytical reasoning supported by interactive visual techniques, which requires interdisciplinary science integrating techniques from visualization and computer graphics, statistics and mathematics, data management and knowledge representation, data analysis and machine learning, cognitive and perceptual sciences.
The main goal of the workshop is to promote Visual Analytics research in Asia-Pacific region, and form a research community to collaboratively solve complex problems arising in a variety of application domains. In particular, special emphasis on the “Big Data” will be addressed.

Aims and Objectives:
This meeting aims to bring world-renowned researchers on Visual Analytics and collaboratively develop innovative scalable Visual Analytics solutions to solve the scalability and complexity issues for analyzing Big Data arising from various application domains including Systems Biology, Social Networks, Finance, Business intelligence, and Security.

Our specific objectives are:

  • We will identify research opportunities in Big Data Visual Analytics, focusing on the Asia-Pacific context.
  • We will form a broader research community with cross-disciplinary collaboration, including computer science, information systems, statistics, biology and sociology, with a focus on 1
    Visual Analytics of Big Data.
  • We will foster greater exchange between visualization researchers and practitioners, and to draw more researchers in the Asia-Pacific region to enter this rapidly growing area of research.
  • We will assist emerging researchers to find linkages to international researchers, industrial contacts, and competitive research grants and fundings.

Significance and Innovation:
Big Data Analytics is the biggest and fundamental challenge in IT research due to Scalability and Complexity. Innovative scalable techniques for Big Data Visual Analytics will be the key enabler for researchers and end users in many application domains and other disciplines.

Expected Outcomes:

  • Innovative techniques and solutions for Big Data Visual Analytics, which will be used by domain experts and end users in various application.
  • Joint publications at the top conferences and journals in Visualization, jointly authored by researchers in the area of Visual Analytics.
  • Joint funding applications for long-term research collaboration for continuation of the research collaboration beyond 2015.

Impact:

  • Academic impact: research publications at top conferences and journals, with high citations.
  • Societal impact: new scalable techniques for Big Data Visual Analytics will be in high-demand by researchers and practitioners in various applications and disciplines to solve complex problems in their domains.