Enhancing Data Understandability. An Integrated Approach

This chapter examines data understandability as a core epistemic condition for democracy and democratic deliberation, arguing that contemporary challenges stem less from data scarcity than from uneven capacities to interpret increasingly complex, AI-mediated information environments. Building on scholarship on visualisation literacy, epistemic inequalities, and the limits of model-centric XAI, the chapter reframes explainability as a matter of sensemaking rather than model disclosure. It theorises narrative scaffolding, critical interactivity, and participatory design as infrastructures capable of contributing to equitable interpretation in civic contexts. The analysis is grounded in two EU projects, KT4D and ORBIS, which operationalise these principles in practice and offer empirical evidence of how visualisation becomes explanation, narrative becomes interpretation, and co-creation becomes a method of democratic alignment.