Personalizing data visualization and interaction

Arjun, S (2018) Personalizing data visualization and interaction. In: 26th ACM InternatiConference on User Modeling, Adaptation and Personalization, UMAP 2018, 8 - 11 July 2018, Singapore, pp. 199-202.

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Abstract

Information visualization is one of the major approach to analyse data. Though there are lot of visualization techniques, designing an adaptive visualization technique for different user and task characteristics is challenging. In this dissertation we are comparing different visualization techniques to find an optimal way for authoring, displaying datasets for two case studies- A crowd sourcing platform for people with different range of abilities and a sensor dashboard for a smart manufacturing set up. We also aspire to develop a user adaptive visualization system. A pilot study found that for numeric dataset, a Bar graph has maximum correct response and Area graph has lowest response time.

Item Type:	Conference Paper
Publication:	UMAP 2018 - Adjunct Publication of the 26th Conference on User Modeling, Adaptation and Personalization
Publisher:	Association for Computing Machinery, Inc
Additional Information:	The copyright for this article belongs to Association for Computing Machinery, Inc
Keywords:	Flow visualization; Information systems; Visualization, Adaptive visualization; Information visualization; Pilot studies; Smart manufacturing; Task characteristics; User interaction; User-adaptive; Visualization technique, Data visualization
Department/Centre:	Division of Mechanical Sciences > Centre for Product Design & Manufacturing
Date Deposited:	08 Aug 2022 11:30
Last Modified:	08 Aug 2022 11:30
URI:	https://eprints.iisc.ac.in/id/eprint/75478

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