Guidance methods have the potential of bringing considerable benefits to Visual Analytics (VA), alleviating the burden on theuser and allowing a positive analysis outcome. However, the boundary between conventional VA approaches and guidance is notsharply defined. As a consequence, framing existing guidance methods is complicated and the development of new approachesis also compromised. In this paper, we try to bring these concepts in order, defining clearer boundaries between guidance andno-guidance. We summarize our findings in form of a decision tree that allows scientists and designers to easily frame theirsolutions. Finally, we demonstrate the usefulness of our findings by applying our guideline to a set of published approaches.
Forschungs-