Digital Humanities at the Intersection of Three Approaches to Data Visualisation: Statistical Graphics, Data Humanism, and Humanistic Interpretation

Digital humanities has a critical role in the progress of the data visualisation field. First, humanities scholars engage with the concept of knowledge as interpretation. Second, they leverage computational tools and statistical methods to analyse and visualise data and metadata. Finally, Digital Humanities projects are a space for experimentation where different epistemic cultures (which often go beyond the Humanities and Computer Science) negotiate new forms of knowledge. Digital Humanities are therefore in a privileged position to benefit from the full potential of data visualisation, using and improving existing methods and tools, and participating in developing those that are much needed but do not yet exist. This article presents a classification of current approaches to data visualisation into (I) statistical
graphics, (II) data humanism and (III) humanistic interpretation. These three approaches are based on four main aspects: a) the intellectual habits around the definition of data, b) the characteristics of the data visualisation and its objectives, c) the relation between the data and the data visualisation, and d) the expected user interaction. The classification is not intended to categorise any data visualisation narrowly, but rather to help navigate the visualisation continuum across epistemological practices. Moreover, based on a large collection of data visualisation examples compiled in an online gallery, several techniques are identified, that
allow to make the transition between the different approaches, potentially
facilitating interdisciplinary projects such as the LuxTIMEMachine, that
leverage multiple types of sources across languages and modalities.