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Rapid development of a data visualization service in an emergency response
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Khan, Saiful, Nguyen, Phong Hai, Abdul-Rahman, Alfie, Freeman, Euan, Turkay, Cagatay and Chen, Min (2022) Rapid development of a data visualization service in an emergency response. IEEE Transactions on Services Computing, 15 (3). pp. 1251-1264. doi:10.1109/TSC.2022.3164146 ISSN 1939-1374.
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Official URL: https://doi.org/10.1109/TSC.2022.3164146
Abstract
We present the design and development of a data visualization service (RAMPVIS) in response to the urgent need to support epidemiological modeling workflows during the COVID-19 pandemic. Facing a set of demanding requirements and several practical challenges, our small team of volunteers had to rely on existing knowledge and components of services computing, while thinking on our feet in configuring services composition and adopting suitable approaches to services engineering. Through developing the RAMPVIS service, we have gained useful experience of ensuring conformation to services computing standards, enabling rapid development and early deployment, and facilitating effective and efficient maintenance and operation with limited resources. This experience can be valuable to the ongoing effort for combating the COVID-19 pandemic, and provides a blueprint for visualization service development when future needs for visual analytics arise during emergency response.
| Item Type: | Journal Article | ||||||||
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| Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine |
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| Divisions: | Faculty of Social Sciences > Centre for Interdisciplinary Methodologies | ||||||||
| Library of Congress Subject Headings (LCSH): | Information visualization, COVID-19 Disease -- Epidemiology -- Data processing, COVID-19 Pandemic, 2020- -- Mathematical models | ||||||||
| Journal or Publication Title: | IEEE Transactions on Services Computing | ||||||||
| Publisher: | IEEE | ||||||||
| ISSN: | 1939-1374 | ||||||||
| Official Date: | 1 May 2022 | ||||||||
| Dates: |
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| Volume: | 15 | ||||||||
| Number: | 3 | ||||||||
| Page Range: | pp. 1251-1264 | ||||||||
| DOI: | 10.1109/TSC.2022.3164146 | ||||||||
| Status: | Peer Reviewed | ||||||||
| Publication Status: | Published | ||||||||
| Reuse Statement (publisher, data, author rights): | © 2022 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 | ||||||||
| Date of first compliant deposit: | 6 May 2022 | ||||||||
| Date of first compliant Open Access: | 6 May 2022 | ||||||||
| RIOXX Funder/Project Grant: |
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