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Propagating visual designs to numerous plots and dashboards
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Khan, Saiful, Nguyen, Phong. H., Abdul-Rahman, Alfie, Benjamin, Bach, Chen, Min, Freeman, Euan and Turkay, Cagatay (2022) Propagating visual designs to numerous plots and dashboards. IEEE Transactions on Visualization and Computer Graphics, 28 (1). pp. 86-95. doi:10.1109/TVCG.2021.3114828
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WRAP-propagating-visual-designs-numerous-plots-dashboards-Turkay-2021.pdf - Accepted Version - Requires a PDF viewer. Download (3088Kb) | Preview |
Official URL: https://doi.org/10.1109/TVCG.2021.3114828
Abstract
In the process of developing an infrastructure for providing visualization and visual analytics (VIS) tools to epidemiologists and modeling scientists, we encountered a technical challenge for applying a number of visual designs to numerous datasets rapidly and reliably with limited development resources. In this paper, we present a technical solution to address this challenge. Operationally, we separate the tasks of data management, visual designs, and plots and dashboard deployment in order to streamline the development workflow. Technically, we utilize: an ontology to bring datasets, visual designs, and deployable plots and dashboards under the same management framework; multi-criteria search and ranking algorithms for discovering potential datasets that match a visual design; and a purposely-design user interface for propagating each visual design to appropriate datasets (often in tens and hundreds) and quality-assuring the propagation before the deployment. This technical solution has been used in the development of the RAMPVIS infrastructure for supporting a consortium of epidemiologists and modeling scientists through visualization.
| Item Type: | Journal Article | ||||||||
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| Alternative Title: | |||||||||
| Subjects: | B Philosophy. Psychology. Religion > BF Psychology Q Science > Q Science (General) Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software |
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| Divisions: | Faculty of Social Sciences > Centre for Interdisciplinary Methodologies | ||||||||
| Library of Congress Subject Headings (LCSH): | Visualization, Visualization -- Technique, Visual analytics, Epidemiology -- Data processing, Ontologies (Information retrieval) , Computer graphics | ||||||||
| Journal or Publication Title: | IEEE Transactions on Visualization and Computer Graphics | ||||||||
| Publisher: | Institute of Electrical and Electronics Engineers | ||||||||
| ISSN: | 1077-2626 | ||||||||
| Official Date: | January 2022 | ||||||||
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| Volume: | 28 | ||||||||
| Number: | 1 | ||||||||
| Page Range: | pp. 86-95 | ||||||||
| DOI: | 10.1109/TVCG.2021.3114828 | ||||||||
| Status: | Peer Reviewed | ||||||||
| Publication Status: | Published | ||||||||
| Reuse Statement (publisher, data, author rights): | © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | ||||||||
| Access rights to Published version: | Restricted or Subscription Access | ||||||||
| RIOXX Funder/Project Grant: |
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