(In conjunction with IEEE VIS 2016, Oct 23th, Baltimore, MD)
The recent ATI (Alan Turing Institute) Symposium on Theoretical Foundation of Visual Analytics identified four aspects of research activities that may contribute directly to the development of a theoretical foundation for Visualization and Visual Analytics. These include taxonomies, principles and guidelines, conceptual frameworks and models, and quantitative laws. For principles and guidelines in visualization and visual analytics, the meeting identified a number of challenges, including:
The objectives of this workshop are:
(i) to support a friendly and open critique of the state of the art of principles and guidelines in Visualization,
(ii) to provide a venue were novel, still in progress, guidelines and principles can be proposed,
(iii) to help define a coherent framework to support existing efforts for the development, validation and conditioning of principles and guidelines,
(iv) to encourage and stimulate new effort towards the development of frameworks for creation and curation of principles and guidelines in Visualization.
The focus of this workshop is placed on a specific yet fundamental aspect which underlines any kind of visualization. While there are established principles and guildeines for other aspects of the visualisation pipeline such as statistics and algorithms (including machine-learned algorithms), and emerging theories for information theory and interaction, there is not yet a unified theoretical foundation or framework for underpinning all four components of creation, curation, critique and conditioning of design guidelines and principles.