TY - GEN
T1 - A Model for Recommending Actions during the Collaborative Design of Visual Analytics Flows
AU - Arce-Orozco, Armando
AU - Gonzalez-Torres, Antonio
AU - Mata-Montero, Erick
AU - Bener, Ayse
AU - Jara-Watson, Hans
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/11
Y1 - 2019/11
N2 - 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.
AB - 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.
KW - Collaborative Visualizations
KW - Recommendation Systems
KW - Visual Analytics
KW - Visual Data Flow
UR - http://www.scopus.com/inward/record.url?scp=85083440496&partnerID=8YFLogxK
U2 - 10.1109/INCISCOS49368.2019.00058
DO - 10.1109/INCISCOS49368.2019.00058
M3 - Contribución a la conferencia
AN - SCOPUS:85083440496
T3 - Proceedings - 2019 International Conference on Information Systems and Computer Science, INCISCOS 2019
SP - 326
EP - 332
BT - Proceedings - 2019 International Conference on Information Systems and Computer Science, INCISCOS 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th International Conference on Information Systems and Computer Science, INCISCOS 2019
Y2 - 20 November 2019 through 22 November 2019
ER -