  Set visualization facilitates the exploration and analysis of set-type data.
However, how sets should be visualized when the data is uncertain is still an
open research challenge. To address the problem of depicting uncertainty in set
visualization, we ask (i) which aspects of set type data can be affected by
uncertainty and (ii) which characteristics of uncertainty influence the
visualization design. We answer these research questions by first developing a
conceptual framework that brings together (i) the information that is primarily
relevant in sets (i.e., set membership, set attributes, and element attributes)
and (ii) different plausible categories of (un)certainty (i.e., certainty,
undefined uncertainty as a binary fact, and defined uncertainty as quantifiable
measure). Based on the conceptual framework, we systematically discuss
visualization examples of integrating uncertainty in set visualizations. We
draw on existing knowledge about general uncertainty visualization and fill
gaps where set-specific aspects have not yet been considered sufficiently.
