Modelling Data Visualization Interactions: from Semiotics to Pragmatics and Back to Humans

Abstract

This paper makes a point of current perspectives on Data Visualization research that were essentially conceived to provide guidelines for finding the best mapping between data and visual representations. Going back to foundational concepts of HCI that rely on manipulation of visual symbols, we propose a new perspective, with the aim to focus on a different configuration, that considers visual signs, professional contexts and user practices. We argue that, so far, user practices have been neglected or left behind in design, evaluation and recommendation scenarios, reducing them to the pure relational focus among kind of data, kind of charts and in lab tasks. This may underestimate the potential of the pragmatic side of this relation, where humans manipulate and interpret signs on the basis of their "practical knowledge, a factor that should be considered to improve human interactions with Data Visualization tools. The perspective discussed here would bring into light and help frame open problems such as interactions in routine tasks and the interpretation of data through visual interactive tools in daily professional practices. By proposing a light but formal model of investigation of these pragmatic interactions, we would like to contribute to the current debate around data visualization as the new strategic tool for dealing with the growing complexity of big data streams, digitization of life, sensor and hardware-embedded intelligence.