The Individual in the Data — the Aspect of Personal Relevance in Designing Casual Data Visualisations

Abstract

Over the last two decades, data visualisation has diffused into the broader realm of mass communication. Before this shift, tools and displays of data-driven geographic- and information visualisation were mostly used in expert contexts. By now, they are also used in casual contexts, for example on newspaper websites, government data portals and many other public outlets. This diversification of the audience poses new challenges within the visualisation community. In this paper we propose personal relevance as one factor to be taken into account when designing casual data visualisations, which are meant for the communication with non-experts. We develop a conceptual model and present a related set of design techniques for interactive web-based visualisations that are aimed at activating personal relevance. We discuss our proposed techniques by applying them to a use case on the visualisation of air pollution in London (UK).

Brooke Leave Home: Designing a Personalized Film to Support Public Engagement with Open Data

“…As a result, the level of individuality that can be presented in terms of data choice and interpretation is limited compared to many of the examples mentioned in the previous section. We observe this might be particularly problematic in the context of experiences for non-expert audiences, as previous work has shown creating personal connections between data and things users care about can be effective in supporting their engagement [42,33,30,24,37,63,22]. Moreover, balancing explanation through narrative and the opportunity to explore based on one's personal perspective has been highlighted as a key design principle of data storytelling [64] -a balance videos identical to all viewers may not strike.…”

Personalisation of data-driven storytelling

“…The term "space", in this context, is understood quite literally as in Tobler's first law of geography: "everything is related to everything else, but near things are more related than distant things" (Tobler 1970). By locating the user in the story space, we can highlight things "closer" and thereby potentially more relevant to the user (see also Meier & Glinka 2017). To construct the user model, we first need to acquire the user's features (see Fig.…”

“…The cases built upon prior conceptual work on the topic (Meier & Glinka 2017, 2018 and were designed to help us investigate the potentials and limitations of the techniques, particularly through user studies, in future research. The two case studies act as real-world tests to see, first of all, if the concept works in general and, second of all, how it could be implemented before conducting further research.…”