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A model for recommending actions during the collaborative design of visual analytics flows
(Institute of Electrical and Electronics Engineers (IEEE) (Estados Unidos), 2019) Arce-Orozco, Armando; González-Torres, Antonio; Mata-Montero, Erick; Bener, Ayse; Jara-Watson, Hans
Abstract. Visual Analytics (VA) is a process to facilitate the uncovering of knowledge from large and complex datasets to enable users to make informed decisions. However, the design of VA tools is frequently performed by multidisciplinary teams that can be physically in the same place or distributed across different locations. Therefore, there is an intrinsic collaboration need between team members and also of proposing methods to support these teams to work collaboratively during the design and implementation of VA systems. Although some proposals have made on the use of visual data flows and recommender systems, its combination with a Multi-Device Environment can benefit the discussion and exchange of knowledge during design and programming. Therefore, this article presents the design of an architecture that combines a Multi-Device Environment (MDE) with visual data flows and recommender systems for the design of VA tools in a collaborative way. The intention is to support designers and programmers during the design of visual data flows through the sharing and analysis of ideas in a collaborative environment supported by a recommender system that aids decision making during the design of flows.