RAMPVIS: Answering the Challenges of Building Visualisation Capabilities for Large-scale Emergency Responses

Min Chen; Alfie Abdul-Rahman; Daniel Archambault; Jason Dykes; Aidan Slingsby; Panagiotis D. Ritsos; Thomas Torsney-Weir; Cagatay Turkay; Benjamin Bach; Rita Borgo; Alys  Brett; Hui Fang; Radu Jianu; Saiful Khan; Robert S. Laramee; Phong H. Nguyen; Richard Reeve; Jonathan C. Roberts; Franck Vidal; Qiru Wang; Jo Wood; Kai Xu

doi:10.1016/j.epidem.2022.100569

RAMPVIS: Answering the Challenges of Building Visualisation Capabilities for Large-scale Emergency Responses

Min Chen
, Alfie Abdul-Rahman
, Daniel Archambault
, Jason Dykes
, Aidan Slingsby
, Panagiotis D. Ritsos
, Thomas Torsney-Weir
, Cagatay Turkay
, Benjamin Bach
, Rita Borgo
, Alys Brett
, Hui Fang
, Radu Jianu
, Saiful Khan
, Robert S. Laramee
, Phong H. Nguyen
, Richard Reeve
, Jonathan C. Roberts
, Franck Vidal
, Qiru Wang

Jo Wood, Kai Xu

Ysgol Cyfrifiadureg a Pheirianneg

Allbwn ymchwil: Cyfraniad at gyfnodolyn › Erthygl › adolygiad gan gymheiriaid

242 Wedi eu Llwytho i Lawr (Pure)

Crynodeb

The effort for combating the COVID-19 pandemic around the world has resulted in a huge amount of data, e.g., from testing, contact tracing, modelling, treatment, vaccine trials, and more. In addition to numerous challenges in epidemiology, healthcare, biosciences, and social sciences, there has been
an urgent need to develop and provide visualisation and visual analytics (VIS) capacities to support emergency responses under difficult operational conditions. In this paper, we report the experience of a group of VIS volunteers who have been working in a large research and development consortium
and providing VIS support to various observational, analytical, model-developmental, and disseminative tasks. In particular, we describe our approaches to the challenges that we have encountered in requirements analysis, data acquisition, visual design, software design, system development, team organisation, and resource planning. By reflecting on our experience, we propose a set of recommendations as the first step towards a methodology for developing and providing rapid VIS capacities to support emergency responses.

Iaith wreiddiol	Saesneg
Rhif yr erthygl	100569
Nifer y tudalennau	15
Cyfnodolyn	Epidemics
Cyfrol	39
Dyddiad ar-lein cynnar	28 Ebr 2022
Dynodwyr Gwrthrych Digidol (DOIs)	https://doi.org/10.1016/j.epidem.2022.100569
Statws	Cyhoeddwyd - Meh 2022

NDC y CU

Mae’r allbwn hwn yn cyfrannu at y Nod(au) Datblygu Cynaliadwy canlynol

Mynediad at Ddogfen

10.1016/j.epidem.2022.100569Trwydded: CC BY

Chen_et_al_RAMVIS_EpidemicsLlawysgrif awdur wedi’i dderbyn, 6.75 MB
RAMPVISFersiwn derfynol wedi’i chyhoeddi, 3.74 MBTrwydded: CC BY

1 Wedi Gorffen

RAMP VIS: Making Visual Analytics an Integral Part of the Technological Infrastructure for Combating COVID-19
Vidal, F. (PY)
1/02/21 → 1/08/22
Project: Ymchwil

2 Cyfraniad i Gynhadledd
2 Erthygl

Challenges and Opportunities in Data Visualization Education: A Call to Action
Bach, B., Keck, M., Rajabiyazdi, F., Losev, T., Meirelles, I., Dykes, J., Laramee, R. S., AlKadi, M., Stoiber, C., Huron, S., Perin, C., Morais, L., Aigner, W., Kosminsky, D., Boucher, M., Knudsen, S., Manataki, A., Aerts, J., Hinrichs, U. & Roberts, J. C. & 1 eraill, Carpendale, S., Ion 2024, Yn: IEEE Transactions on visualization and computer graphics. 30, t. 649-660 12 t.
Allbwn ymchwil: Cyfraniad at gyfnodolyn › Erthygl › adolygiad gan gymheiriaid

Mynediad agored
Ffeil
80 Wedi eu Llwytho i Lawr (Pure)
RAMPVIS: Answering the Challenges of Building Visualization Capabilities for Large-scale Emergency Responses
Chen, M., Abdul-Rahman, A., Archambault, D., Dykes, J., Ritsos, P. D., Slingsby, A., Torsney-Weir, T., Turkay, C., Bach, B., Borgo, R., Brett, A., Fang, H., Jianu, R., Khan, S., Laramee, R. S., Matthews, L., Nguyen, P. H., Reeve, R., Roberts, J. C. & Vidal, F. & 3 eraill, Wang, Q., Wood, J. & Xu, K., Hyd 2023, IEEE VIS Workshop on Visualization for Pandemic and Emergency Responses 2023 (Vis4PandEmRes). IEEE
Allbwn ymchwil: Pennod mewn Llyfr/Adroddiad/Trafodion Cynhadledd › Cyfraniad i Gynhadledd › adolygiad gan gymheiriaid
Visual Analytics based Search-Analyze-Forecast Framework for Epidemiological Time-series Data
Gönen, T., Xing, Y., Turkay, C., Abdul-Rahman, A., Jianu, R., Fang, H., Freeman, E., Vidal, F. & Chen, M., Hyd 2023, IEEE VIS Workshop on Visualization for Pandemic and Emergency Responses 2023 (Vis4PandEmRes). IEEE
Allbwn ymchwil: Pennod mewn Llyfr/Adroddiad/Trafodion Cynhadledd › Cyfraniad i Gynhadledd › adolygiad gan gymheiriaid

1 Cymryd rhan mewn cynhadledd Academaidd

EduVis : Workshop on Visualization Education, Literacy, and Activities
Keck, M. (Cadeirydd), Huron, S. (Cadeirydd), Panagiotidou, G. (Cadeirydd), Stoiber, C. (Cadeirydd), Rajabiyazdi, F. (Cadeirydd), Perin, C. (Cadeirydd), Roberts, J. (Cadeirydd) & Bach, B. (Cadeirydd)
22 Hyd 2023 → 27 Hyd 2023
Gweithgaredd: Cymryd rhan mewn digwyddiad neu drefnu digwyddiad › Cymryd rhan mewn cynhadledd Academaidd

Dyfynnu hyn

Chen, M., Abdul-Rahman, A., Archambault, D., Dykes, J., Slingsby, A., Ritsos, P. D., Torsney-Weir, T., Turkay, C., Bach, B., Borgo, R., Brett, A., Fang, H., Jianu, R., Khan, S., Laramee, R. S., Nguyen, P. H., Reeve, R., Roberts, J. C., Vidal, F., ... Xu, K. (2022). RAMPVIS: Answering the Challenges of Building Visualisation Capabilities for Large-scale Emergency Responses. Epidemics, 39, erthygl 100569. https://doi.org/10.1016/j.epidem.2022.100569

@article{3eec06316aec42b2b24aec712745f652,

title = "RAMPVIS: Answering the Challenges of Building Visualisation Capabilities for Large-scale Emergency Responses",

abstract = "The effort for combating the COVID-19 pandemic around the world has resulted in a huge amount of data, e.g., from testing, contact tracing, modelling, treatment, vaccine trials, and more. In addition to numerous challenges in epidemiology, healthcare, biosciences, and social sciences, there has been an urgent need to develop and provide visualisation and visual analytics (VIS) capacities to support emergency responses under difficult operational conditions. In this paper, we report the experience of a group of VIS volunteers who have been working in a large research and development consortium and providing VIS support to various observational, analytical, model-developmental, and disseminative tasks. In particular, we describe our approaches to the challenges that we have encountered in requirements analysis, data acquisition, visual design, software design, system development, team organisation, and resource planning. By reflecting on our experience, we propose a set of recommendations as the first step towards a methodology for developing and providing rapid VIS capacities to support emergency responses.",

keywords = "Data visualisation, Visual Analytics, Pandemic responses, COVID-19, Model development",

author = "Min Chen and Alfie Abdul-Rahman and Daniel Archambault and Jason Dykes and Aidan Slingsby and Ritsos, \{Panagiotis D.\} and Thomas Torsney-Weir and Cagatay Turkay and Benjamin Bach and Rita Borgo and Alys Brett and Hui Fang and Radu Jianu and Saiful Khan and Laramee, \{Robert S.\} and Nguyen, \{Phong H.\} and Richard Reeve and Roberts, \{Jonathan C.\} and Franck Vidal and Qiru Wang and Jo Wood and Kai Xu",

year = "2022",

month = jun,

doi = "10.1016/j.epidem.2022.100569",

language = "English",

volume = "39",

journal = "Epidemics",

issn = "1755-4365",

publisher = "Elsevier",

}

Chen, M, Abdul-Rahman, A, Archambault, D, Dykes, J, Slingsby, A, Ritsos, PD, Torsney-Weir, T, Turkay, C, Bach, B, Borgo, R, Brett, A, Fang, H, Jianu, R, Khan, S, Laramee, RS, Nguyen, PH, Reeve, R, Roberts, JC , Vidal, F, Wang, Q, Wood, J & Xu, K 2022, 'RAMPVIS: Answering the Challenges of Building Visualisation Capabilities for Large-scale Emergency Responses', Epidemics, cyfrol. 39, 100569. https://doi.org/10.1016/j.epidem.2022.100569

TY - JOUR

T1 - RAMPVIS: Answering the Challenges of Building Visualisation Capabilities for Large-scale Emergency Responses

AU - Chen, Min

AU - Abdul-Rahman, Alfie

AU - Archambault, Daniel

AU - Dykes, Jason

AU - Slingsby, Aidan

AU - Ritsos, Panagiotis D.

AU - Torsney-Weir, Thomas

AU - Turkay, Cagatay

AU - Bach, Benjamin

AU - Borgo, Rita

AU - Brett, Alys

AU - Fang, Hui

AU - Jianu, Radu

AU - Khan, Saiful

AU - Laramee, Robert S.

AU - Nguyen, Phong H.

AU - Reeve, Richard

AU - Roberts, Jonathan C.

AU - Vidal, Franck

AU - Wang, Qiru

AU - Wood, Jo

AU - Xu, Kai

PY - 2022/6

Y1 - 2022/6

N2 - The effort for combating the COVID-19 pandemic around the world has resulted in a huge amount of data, e.g., from testing, contact tracing, modelling, treatment, vaccine trials, and more. In addition to numerous challenges in epidemiology, healthcare, biosciences, and social sciences, there has been an urgent need to develop and provide visualisation and visual analytics (VIS) capacities to support emergency responses under difficult operational conditions. In this paper, we report the experience of a group of VIS volunteers who have been working in a large research and development consortium and providing VIS support to various observational, analytical, model-developmental, and disseminative tasks. In particular, we describe our approaches to the challenges that we have encountered in requirements analysis, data acquisition, visual design, software design, system development, team organisation, and resource planning. By reflecting on our experience, we propose a set of recommendations as the first step towards a methodology for developing and providing rapid VIS capacities to support emergency responses.

AB - The effort for combating the COVID-19 pandemic around the world has resulted in a huge amount of data, e.g., from testing, contact tracing, modelling, treatment, vaccine trials, and more. In addition to numerous challenges in epidemiology, healthcare, biosciences, and social sciences, there has been an urgent need to develop and provide visualisation and visual analytics (VIS) capacities to support emergency responses under difficult operational conditions. In this paper, we report the experience of a group of VIS volunteers who have been working in a large research and development consortium and providing VIS support to various observational, analytical, model-developmental, and disseminative tasks. In particular, we describe our approaches to the challenges that we have encountered in requirements analysis, data acquisition, visual design, software design, system development, team organisation, and resource planning. By reflecting on our experience, we propose a set of recommendations as the first step towards a methodology for developing and providing rapid VIS capacities to support emergency responses.

KW - Data visualisation

KW - Visual Analytics

KW - Pandemic responses

KW - COVID-19

KW - Model development

U2 - 10.1016/j.epidem.2022.100569

DO - 10.1016/j.epidem.2022.100569

M3 - Article

SN - 1755-4365

VL - 39

JO - Epidemics

JF - Epidemics

M1 - 100569

ER -

RAMPVIS: Answering the Challenges of Building Visualisation Capabilities for Large-scale Emergency Responses

Crynodeb

NDC y CU

Mynediad at Ddogfen

Ôl bys

Prosiectau

RAMP VIS: Making Visual Analytics an Integral Part of the Technological Infrastructure for Combating COVID-19

Allbwn Ymchwil

Challenges and Opportunities in Data Visualization Education: A Call to Action

RAMPVIS: Answering the Challenges of Building Visualization Capabilities for Large-scale Emergency Responses

Visual Analytics based Search-Analyze-Forecast Framework for Epidemiological Time-series Data

Gweithgareddau

EduVis : Workshop on Visualization Education, Literacy, and Activities

Dyfynnu hyn