The global population is growing at an incomprehensible rate and with it come complex environmental consequences that often result in social injustices. The United Nations has established a set of Sustainable Development Goals (SDGs) in an attempt to ameliorate inequality and promise safety for the masses. To reach these goals, a set of indicators have been identified and their associated data for each country are publicly available to measure how close each country is to each goal. Multifaceted social and environmental processes that are difficult to understand are causing threats to these goals. Maps help reduce complexity. Now, arguably anyone with access to the Internet and time can make a map. However, not all maps are effective accurate communication vessels. Well-designed maps tell a story that truthfully represents the data available. Here we present a synthesis of the cartographic workflow pointing out specific considerations necessary when mapping SDG indicators. Along the way we illustrate the cartographic workflow as it relates to visualizing SDG indicators. Common mapping pitfalls are described and a range of suggestions to avoid them are also offered. Map makers have a unique opportunity to use these data to illuminate and communicate injustices that are documented therein to inspire creative localized solutions to eradicate inequality.

A ‘universal grammar’ for the full spectrum of visualization types is discussed. The grammar enables the analysis of any type of visualization regarding its syntactic constituents, such as the types of visual encodings and visual components that are used. Such an analysis of a type of visualization, describing its compositional syntax, can be represented as a specification tree. Colour coded tree branches between constituent types enforce the combination rules visually. We discuss how these specification trees differ from linguistic parse trees, and how visual statements differ from verbal statements. The grammar offers a basis for generating visualization options, and the potential for formalization and for machine-readable specifications. This may serve as a basis for a system providing computer-generated visualization advice.