Contribute to our special issue on Human Centric Visual Analytics
摘要截稿:
全文截稿: 2018-04-30
影响因子: 1.781
期刊难度:
CCF分类: C类
中科院JCR分区:
• 大类 : 管理学 - 4区
• 小类 : 计算机:控制论 - 4区
• 小类 : 人体工程学 - 4区
Overview
With the rapid advancement of storage media and network technologies, the data we need to deal with in various situations has become increasingly large and complex. To make sense of such large and complex datasets, many automatic analytical methods have been developed.
Visual analytics combines these automatic methods and visual interactions with a tight coupling between human cognition and computational power and has quickly emerged as a major trend for business intelligence with an increasingly important role in fulfilling data-driven objectives.
The development of new tools and products in this area have focused on mining data patterns and making the hidden information visible to users. Relatively less attention has been paid on how this information should be presented so that the end users can effectively comprehend it for problem solving and decision making.
In other words, current analytical systems focus more on the computer side while strong presence of “human-in-the loop” is missing. This imbalance between human and computer has resulted in the lack of theories and guidelines for system design and evaluation and prevented systems and tools from being more useful in practice.
This specie issue aims to shine a light on this issue by publishing visualization theories, novel design principles, analytics techniques and evaluation methodologies that are to address issues surrounding human-centric visual analytics. The primary objective is to foster focused attention in this emerging area and to serve as forum for researchers and professionals all over the world to exchange and discuss the latest advances.
What can I contribute
Papers to be submitted to this special issue must focus on the human side of visual analytics. We will support papers that explore the following:
- Visual perception and cognition
- Design principle and guidelines for human-centric visual analytics
- New evaluation methodologies and metrics
- New visualization and visual analytics theories.
- Adaption and refinement of existing theories and principles from HCI and Psychology in human–centric visual analytics
- Novel human-data interfaces, frameworks, reference models, architectures, tools and systems
- New human-data, human-computer and human-human interaction methods in the context of visual analytics
- Human, social and cultural factors in collaborative visual analytics