RAMPVIS: Answering the challenges of building visualisation capabilities for large-scale emergency responses

被引:8
|
作者
Chen, M. [1 ]
Abdul-Rahman, A. [2 ]
Archambault, D. [3 ]
Dykes, J. [4 ]
Ritsos, P. D. [5 ]
Slingsby, A. [4 ]
Torsney-Weir, T. [3 ]
Turkay, C. [6 ]
Bach, B. [7 ]
Borgo, R. [2 ]
Brett, A. [8 ]
Fang, H. [9 ]
Jianu, R. [4 ]
Khan, S. [1 ,10 ]
Laramee, R. S. [11 ]
Matthews, L. [12 ]
Nguyen, P. H. [13 ]
Reeve, R. [12 ]
Roberts, J. C. [5 ]
Vidal, F. P. [5 ]
Wang, Q. [11 ]
Wood, J. [4 ]
Xu, K. [14 ]
机构
[1] Univ Oxford, Oxford, England
[2] Kings Coll London, London, England
[3] Swansea Univ, Swansea, Wales
[4] Univ London, London, England
[5] Bangor Univ, Bangor, Wales
[6] Univ Warwick, Coventry, W Midlands, England
[7] Univ Edinburgh, Edinburgh, Scotland
[8] UK Atom Energy Author, Oxford, England
[9] Loughborough Univ, Loughborough, England
[10] Horus Secur Consultancy Ltd, Oxford, England
[11] Univ Nottingham, Nottingham, England
[12] Univ Glasgow, Glasgow, Scotland
[13] Red Sift Ltd, London, England
[14] Middlesex Univ London, London, England
基金
英国工程与自然科学研究理事会;
关键词
Data visualisation; Visual analytics; Pandemic responses; COVID-19; Model development; DECISION-SUPPORT; VISUAL ANALYTICS; DESIGN; UNCERTAINTY; FLOW; DASHBOARDS; TOOL;
D O I
10.1016/j.epidem.2022.100569
中图分类号
R51 [传染病];
学科分类号
100401 ;
摘要
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.
引用
收藏
页数:15
相关论文
共 50 条
  • [1] Emergency Logistics in a Large-Scale Disaster Context: Achievements and Challenges
    Jiang, Yiping
    Yuan, Yufei
    INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2019, 16 (05)
  • [2] Building IT Capabilities to Deploy Large-Scale Synchronous Online Technology in Teaching and Learning
    Low, Stephen
    Goh, Jenson
    Kiu, Yeung Sze
    Chia, Ivy
    HCI IN BUSINESS, GOVERNMENT, AND ORGANIZATIONS: ECOMMERCE AND INNOVATION, PT I, 2016, 9751 : 531 - 544
  • [3] Regional response to large-scale emergency events: Building on historical data
    Romanowski, Carol
    Raj, Rajendra
    Schneider, Jennifer
    Mishra, Sumita
    Shivshankar, Vinay
    Ayengar, Srikant
    Cueva, Fernando
    INTERNATIONAL JOURNAL OF CRITICAL INFRASTRUCTURE PROTECTION, 2015, 11 : 12 - 21
  • [4] Relief supply collaboration for emergency logistics responses to large-scale disasters
    Sheu, Jiuh-Biing
    Pan, Cheng
    TRANSPORTMETRICA A-TRANSPORT SCIENCE, 2015, 11 (03) : 210 - 242
  • [5] Towards Visualisation of Resilience Assessment for Large-Scale Systems
    Troubitsyna, Elena
    Laibinis, Linas
    2015 IEEE 17TH INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE COMPUTING AND COMMUNICATIONS, 2015 IEEE 7TH INTERNATIONAL SYMPOSIUM ON CYBERSPACE SAFETY AND SECURITY, AND 2015 IEEE 12TH INTERNATIONAL CONFERENCE ON EMBEDDED SOFTWARE AND SYSTEMS (ICESS), 2015, : 924 - 924
  • [6] Topology visualisation tool for large-scale communications networks
    Guo, Y.
    Chen, C.
    Zhou, S.
    ELECTRONICS LETTERS, 2007, 43 (10) : 597 - 598
  • [7] Large-scale comparative visualisation of sets of multidimensional data
    Vohl, Dany
    Barnes, David G.
    Fluke, Christopher J.
    Poudel, Govinda
    Georgiou-Karistianis, Nellie
    Hassan, Amr H.
    Benovitski, Yuri
    Wong, Tsz Ho
    Kaluza, Owen L.
    Nguyen, Toan D.
    Bonnington, C. Paul
    PEERJ COMPUTER SCIENCE, 2016,
  • [8] Large-scale agricultural investment in Ethiopia: Development, challenges and policy responses
    Abesha, Nebiyu
    Assefa, Engdawork
    Petrova, Maria A.
    LAND USE POLICY, 2022, 117
  • [9] Responses in large-scale structure
    Barreira, Alexandre
    Schmidt, Fabian
    JOURNAL OF COSMOLOGY AND ASTROPARTICLE PHYSICS, 2017, (06):
  • [10] Building large-scale Bayesian networks
    Neil, M
    Fenton, N
    Nielsen, L
    KNOWLEDGE ENGINEERING REVIEW, 2000, 15 (03): : 257 - 284