Supporting Decision Making during Emergencies through Information Visualization of Crowdsourcing Emergency Data

被引:0
作者
Simoes Jr, Paulo [1 ]
Raimundo, Pedro O. [1 ]
Novais, Renato [2 ,3 ]
Vieira, Vaninha [1 ,3 ]
Mendonca, Manoel [1 ,3 ]
机构
[1] Univ Fed Bahia, Dept Comp Sci, Av Adhemar Barros, Salvador, BA, Brazil
[2] Fed Inst Bahia, Dept Comp Sci, Rua Emidio Santos, Salvador, BA, Brazil
[3] Univ Fed Bahia, Fraunhofer Project, Ctr Software & Syst Engn, Av Paralela, Salvador, BA, Brazil
来源
ICEIS: PROCEEDINGS OF THE 19TH INTERNATIONAL CONFERENCE ON ENTERPRISE INFORMATION SYSTEMS - VOL 3 | 2017年
关键词
Emergency Management; Information Visualization; Crowdsourcing; Decision Support;
D O I
10.5220/0006370701780185
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Decision making during an emergency response requires having the right information provided in the right way to the right people. Relevant information about an emergency can be provided by several sources, including the crowd at the place where the emergency is happening. A big challenge is how to avoid overwhelming the decision makers with unnecessary or redundant information provided by the crowd. Our hypothesis is that appropriate information visualization techniques improve the understanding of information sent by a crowd during an emergency. This work presents an approach for emergency information visualization, gathered through crowdsourcing, which improves context-aware decision making by keeping a real-time emergency state board. This approach was implemented in ERTK, as a proof of concept, and evaluated with 15 emergency management experts in Brazil. The yielded results show that our approach has the potential to assist a context-aware decision making during an emergency response.
引用
收藏
页码:178 / 185
页数:8
相关论文
共 40 条
[21]   Towards the development of a decision support system for multi-agency decision-making during cross-border emergencies [J].
Neville, Karen ;
O'Riordan, Sheila ;
Pope, Andrew ;
Rauner, Marion ;
Rochford, Maria ;
Madden, Martina ;
Sweeney, James ;
Nussbaumer, Alexander ;
McCarthy, Nora ;
O'Brien, Cian .
JOURNAL OF DECISION SYSTEMS, 2016, 25 :381-396
[22]   Supporting Decision-Making in the Building Life-Cycle Using Linked Building Data [J].
Pauwels, Pieter .
BUILDINGS, 2014, 4 (03) :549-579
[23]   BigPromises: using organisational mindfulness to integrate big data in emergency management decision making [J].
Amaye, Alexis ;
Neville, Karen ;
Pope, Andrew .
JOURNAL OF DECISION SYSTEMS, 2016, 25 :76-84
[24]   Integrated information visualization to support decision making for use of antibiotics in intensive care: design and usability evaluation [J].
Forsman, Johanna ;
Anani, Nadim ;
Eghdam, Aboozar ;
Falkenhav, Magnus ;
Koch, Sabine .
INFORMATICS FOR HEALTH & SOCIAL CARE, 2013, 38 (04) :330-353
[25]   Supporting Cognition in the Face of Political Data and Discourse: A Mental Models Perspective on Designing Information Visualization Systems [J].
Schreder, Guenther ;
Windhager, Florian ;
Smuc, Michael ;
Mayr, Eva .
PROCEEDINGS OF THE SIXTH INTERNATIONAL CONFERENCE FOR E-DEMOCRACY AND OPEN GOVERNMENT, (CEDEM16), 2016, :213-218
[26]   Valparaiso's 2014 Fire: Evaluation of Environmental and Epidemiological Risk Factors During the Emergency Through a Crowdsourcing Tool [J].
Espinoza Espinoza, Sebastian Eduardo ;
Vivaceta De la Fuente, Anibal Enrique ;
Machuca Contreras, Constanza Andrea .
DISASTER MEDICINE AND PUBLIC HEALTH PREPAREDNESS, 2017, 11 (02) :239-243
[27]   A new emergency management dynamic value assessment model based on social media data: a multiphase decision-making perspective [J].
Shan, Siqing ;
Liu, Xiaohui ;
Wei, Yigang ;
Xu, Lida ;
Zhang, Baishang ;
Yu, Lei .
ENTERPRISE INFORMATION SYSTEMS, 2020, 14 (05) :680-709
[28]   Multidimensional risk evaluation: Information visualization to support a decision-making process in the context of natural gas pipeline [J].
Medeiros, C. ;
Alencar, M. H. ;
Garcez, T. V. ;
de Almeida, A. T. .
RISK, RELIABILITY AND SAFETY: INNOVATING THEORY AND PRACTICE, 2017, :2922-2928
[29]   Current state of the art and future directions: Augmented reality data visualization to support decision-making [J].
Zheng, Mengya ;
Lillis, David ;
Campbell, Abraham G. .
VISUAL INFORMATICS, 2024, 8 (02) :80-105
[30]   The Expert System Supporting Decision-Making in the Process of Vegetable Pests Extermination During Vegetation Period [J].
Sojak, Mariusz ;
Glowacki, Szymon ;
Tulej, Weronika ;
Brys, Andrzej ;
Hutsol, Taras ;
Horetska, Iryna ;
Stroianovska, Liliia ;
Rozkosz, Anna ;
Pristavka, Miroslav .
AGRICULTURAL ENGINEERING-POLAND, 2023, 27 (01) :331-348