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Poster De Conférence Année : 2017

DataTours: A Data Narratives Framework

Résumé

Visual storytelling is commonly employed to communicate data analyses results. Alternatively, (semi-)automated [1, 2, 6] data narratives or " tours " have been proposed as a means to prompt exploration of massive multidimensional datasets, substituting the more prevalent static overviews. While these works demonstrate specific instances of data tours, a concrete model to describe the building blocks of such tours is lacking. We present a descriptive hierarchical framework, DataTours, to formalize and guide the design of (semi-) automated tours for data exploration and discuss challenges evoked by the framework in the (semi-)automated authoring of such tours.
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Dates et versions

hal-01655433 , version 1 (04-12-2017)

Identifiants

  • HAL Id : hal-01655433 , version 1

Citer

Hrim Mehta, Amira Chalbi, Fanny Chevalier, Christopher Collins. DataTours: A Data Narratives Framework. IEEE InfoVis 2017 - IEEE Information Visualization conference, Oct 2017, Phoenix, United States. pp.1-2. ⟨hal-01655433⟩
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