Filtering is one of the basic interaction techniques in Information Visualization, with the main objective of limiting the amount of displayed information using constraints on attribute values. Research focused on direct manipulation selection means or on simple interactors like sliders or check-boxes: while the interaction with a single attribute is, in principle, straightforward, getting an understanding of the relationship between multiple attribute constraints and the actual selection might be a complex task. To cope with this problem, usually referred as cross-filtering, the paper provides a general definition of the structure of a filter, based on domain values and data distribution, the identification of visual feedbacks on the relationship between filters status and the current selection, and guidance means to help in fulfilling the requested selection. Then, leveraging on the definition of these design elements, the paper proposes CrossWidgets, modular attribute selectors that provide the user with feedback and guidance during complex interaction with multiple attributes. An initial controlled experiment demonstrates the benefits that CrossWidgets provide to cross-filtering activities.

CrossWidgets: Enhancing Complex Data Selections through Modular Multi Attribute Selectors / Angelini, M.; Blasilli, G.; Lenti, S.; Palleschi, A.; Santucci, G.. - (2020), pp. 1-9. (Intervento presentato al convegno 2020 International Conference on Advanced Visual Interfaces, AVI 2020 tenutosi a Island of Ischia, ita) [10.1145/3399715.3399918].

CrossWidgets: Enhancing Complex Data Selections through Modular Multi Attribute Selectors

Angelini M.;Blasilli G.;Lenti S.;Palleschi A.;Santucci G.
2020

Abstract

Filtering is one of the basic interaction techniques in Information Visualization, with the main objective of limiting the amount of displayed information using constraints on attribute values. Research focused on direct manipulation selection means or on simple interactors like sliders or check-boxes: while the interaction with a single attribute is, in principle, straightforward, getting an understanding of the relationship between multiple attribute constraints and the actual selection might be a complex task. To cope with this problem, usually referred as cross-filtering, the paper provides a general definition of the structure of a filter, based on domain values and data distribution, the identification of visual feedbacks on the relationship between filters status and the current selection, and guidance means to help in fulfilling the requested selection. Then, leveraging on the definition of these design elements, the paper proposes CrossWidgets, modular attribute selectors that provide the user with feedback and guidance during complex interaction with multiple attributes. An initial controlled experiment demonstrates the benefits that CrossWidgets provide to cross-filtering activities.
2020
2020 International Conference on Advanced Visual Interfaces, AVI 2020
crossfilter; user feedback; visual filtering; visual guidance
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
CrossWidgets: Enhancing Complex Data Selections through Modular Multi Attribute Selectors / Angelini, M.; Blasilli, G.; Lenti, S.; Palleschi, A.; Santucci, G.. - (2020), pp. 1-9. (Intervento presentato al convegno 2020 International Conference on Advanced Visual Interfaces, AVI 2020 tenutosi a Island of Ischia, ita) [10.1145/3399715.3399918].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1486475
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