Turning data into visual form that reads clearly, choosing what fits the purpose and blocking misreadings.
Data visualization loads numbers onto visual channels like position, length, color, and shape so people can read them. You decide what to show, pick a visual encoding that suits the data type, strip out the misreadings that axes and colors create, and check that the same information reaches readers who can't see the picture. The weight sits on designing and delivering a chart that will be read, not on reading and interpreting one.
Defines data visualization literacy and structures it into conceptual frameworks, exercises, and assessments. It is the primary basis for the level boundary where reading ability turns into design ability.
A psychometrically validated instrument that measures 8 visualization tasks across 12 chart types with 53 items. The list of tasks those items cover gives the lower level checklists their concrete basis.
A standard typology that sorts visualization tasks into why, how, and what layers. It supplies the vocabulary and the criteria for the design decisions the upper levels demand.
An international standard requiring charts and diagrams to carry both a short identifying alt text and a long description covering values, trends, and relationships. It grounds the L3-L5 items on delivery and misreading, which check that information lands without a visual channel.
The classic experiment establishing that reading accuracy differs across elementary perceptual tasks. It backs the point that choosing which value rides on which visual channel is a measurable question, not a matter of taste. Upper levels apply the same standard to rule evidence and to testing new forms.
