Ceneda, DavideGschwandtner, TheresiaMay, ThorstenMiksch, SilviaStreit, MarcTominski, ChristianChristian Tominski and Tatiana von Landesberger2018-06-022018-06-022018978-3-03868-064-2https://doi.org/10.2312/eurova.20181107https://diglib.eg.org:443/handle/10.2312/eurova20181107Guidance methods have the potential of bringing considerable benefits to Visual Analytics (VA), alleviating the burden on the user and allowing a positive analysis outcome. However, the boundary between conventional VA approaches and guidance is not sharply defined. As a consequence, framing existing guidance methods is complicated and the development of new approaches is also compromised. In this paper, we try to bring these concepts in order, defining clearer boundaries between guidance and no-guidance. We summarize our findings in form of a decision tree that allows scientists and designers to easily frame their solutions. Finally, we demonstrate the usefulness of our findings by applying our guideline to a set of published approaches.Humancentered computingVisual analyticsVisualization theoryconcepts and paradigmsInformation systemsDecision support systems10.2312/eurova.2018110719-23