Defining Data Visualisation
Dispute in definitions
Given the growing multitude of inter-disciplinary practitioners and the wide variety of work produced by them, it’s no surprise that the definition of data visualisation is in flux. Different groups emphasise what matters to them & to their audience. Some focus on the visual & aesthetic nature of the work while others treat visualisations as a purely cognitive tool, as outlined by Steven Braun in his paper . A dispute in definitions is a sign of a field undergoing a creative boom and I would love to add my own to the mix.
The majority of information graphics, for instance, are shaped by the disciplines from which they have sprung: statistics, empirical sciences, and business. Can these graphic languages serve humanistic fields where interpretation, ambiguity, inference, and qualitative judgment take priority over quantitative statements and presentations of “facts”?
— Johanna Drucker, Graphesis: Visual Forms of Knowledge Production 
The essence of data visualisation, I contend, is neither about data nor visualisation.
It’s not about data
A visualisation should be driven not by the available data but by the surrounding context of the people and their stories. By losing sight of the context, a practitioner is at the risk of ignoring non-quantitative sources of information and its potential to add colour & richness to a visualisation. Devoid of a narrative, a visualisation becomes flat & loses its capacity to invoke empathy. Data is a means to an end & is only as valuable as its ability to answer our questions about our world.
It’s not about visualisation
We navigate and understand the world through all our senses & not just the visual sense. An over emphasis on visualisation takes away other means of making data concrete & accessible to all our senses. The ambiguous, sensory, and emotional nature of the human experience compels us to look beyond objective & visual representation of data. While valuable and appealing to the eye, an over emphasis on the visual sense limits the work to flat forms devoid of material or space and a stunted notion of interactivity. A multi-sensory approach holds the potential to create visceral, intriguing, and more memorable experiences.
So, here is my two penny definition of data visualisation: A humanist approach to understanding & narrating stories seen through the lens of data that encourages sense-making by engaging with multi-sensory & transmedia experiences.
 Braun, S. (2017) Data Visualisation for Success. Images Publishing.
 Drucker, Johanna. (2014) Graphesis: Visual Forms of Knowledge Production. Harvard University Press.