IEEE Computer Graphics and Applications
Personal Visualization and Personal Visual Analytics
Final submissions due: 1 November 2014
Publication date: July/August 2015
For each and every one of us as individuals, big data impinges on our personal lives as well as our professional lives. This includes our social networks, our expanding photo collections, and our intentions to become more green. Application of visualization and visual analytics to our personal context offers substantial opportunity to help individuals gain insight and knowledge about themselves and their communities, ranging from health and fitness information, to music listening histories, to records of their interactions with others through social media.
However, designing tools to support the analysis of data in one's nonprofessional life brings a unique set of research and design challenges. Personal visualization is the study of how these changing research and design challenges lead to new explorations into visual representation. Personal visual analytics (PVA) is the science of analytical reasoning facilitated by visual representations used within a personal context. PVA extends visual analytics to the personal domain and aims to empower individuals in their everyday lives to develop insights and discover knowledge relevant to their personal lives. Personal context implies a nonprofessional situation, where people may have different goals, priorities, role expectations, environments, or time and resource budgets than in professional aspects of their lives.
The July/August 2015 issue of IEEE Computer Graphics and Applications will be devoted to Personal Visualization and Personal Visual Analytics. For this special issue, we solicit papers describing visualization and visual analytics applications designed for use in a personal context, plus discussions of fundamental issues important to the design, development, and success of PVA tools.
We welcome papers on a variety of topics, including:
- fundamental issues important to the design of PVA systems (including design issues for home and mobile use contexts, design for visualization and analytics novices, design for low-attentional demand, and so on);
- real-world experiences with designing, building, deploying and evaluating personal visualization and visual analytic systems;
- case studies describing success (and failure) of applying visualization and visual analytics in a personal context; and
- review and evaluation papers discussing or comparing current tools, techniques, and design considerations.
We welcome papers from both commercial and academic sources; from researchers as well as practitioners.
Articles should be no more than eight magazine pages, where a page is 800 words and a quarter — page image counts as 200 words. References are not restricted, but please limit your citations to the most relevant ones. Also consider providing technical background in sidebars for nonexpert readers. Color images are preferable and should be limited to 10. Visit the CG&A style and length guidelines at www.computer.org/web/peerreviewmagazines/cga. We also strongly encourage you to submit multimedia (videos, podcasts, and so on) to enhance your article. Visit CG&A supplemental guidelines at www.computer.org/web/peerreviewmagazines/accga#supplemental.
Please submit your paper using the online manuscript submission service at https://mc.manuscriptcentral.com/cs-ieee.
When uploading your paper, select the appropriate special-issue title under the category "Manuscript Type." Also, include complete contact information for all authors. If you have any questions about submitting your article, contact the peer review coordinator at firstname.lastname@example.org.
Please direct any correspondence before submission to the guest editors: