IVAS: Improving Visual Analytics Systems

IVAS is an ontological framework for supporting the gradual development of a comprehensive ontology that records the problems and solutions in improving visual analytics (VA) systems. The framework was first described in the following research paper:

M. Chen and D. S. Ebert. "An ontological framework for supporting the design and evaluation of visual analytics systems." Computer Graphics Forum, 38(3):131-144, 2019. DOI: http://dx.doi.org/10.1111/cgf.13677. (Presented at EuroVis 2019.) 

USING IVAS

A system designer may use IVAS during requirement analysis to analyse different symptoms of the current VA workflow, cogitate likely causes, deliberate possible remedies, and anticipate potential side-effects. A UX analyst may use IVAS to conduct initial assessment of a VA system , identify potentially critical issues for to be evaluated in detail using empirical methods, such as observational studies and small group discussions. A senior manager or a project reviewer may use IVAS to aid the reading and appraising of a report about a VA system.

CONTRIBUTING TO IVAS

IVAS, especially its lists of concrete entities, is an ongoing development, and can benefit tremendously from your contributions in terms of time and knowledge. If you have noticed any missing records of certain symptoms, causes, and remedies in improving VA systems, any missing causal relationships between symptoms and causes, between causes and remedies, and between remedies and side-effects, please to click the Contribute text here or press the Contribute button on the top of this page.  We will acknowledge your contribution by listing you a contributor.