Uncertain infographics: Expressing doubt in data visualization

Abstract The myth of transparency and truthfulness is the foundation for contemporary theories of information design. Avoiding distortion and ambiguity is the moral imperative of an upstanding data visualizer. Sometimes, though, data that is collected is not accurate enough and the sources use indirect indicators to approach a phenomenon: what to do then, if the need to graphically represent a phenomenon is urgent and necessary? Should the designer wait to have the exact data, or should he indicate a trend, expressing the hypothetical status of his statement? Can data visualization be designed to express doubt rather than to inform about facts? This essay will deal with the forms of expression of uncertainty in infographics. It will consider the designer as both an observer and a translator, whose position of neutrality is only one of the possible realms of discourse. In general, it will focus on the forms of visual expression of a self-criticizing mood in quantitative research today and it will explore the ways in which data that is not meaningful in statistical terms can become meaningful in semiotic terms.