Zeno Franco, José J. González, & José H. Canós. (2019). Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management (Z. Franco, J. J. González, & J. H. Canós, Eds.). Valencia, Spain: Iscram.
Abstract: The theme of ISCRAM 2019 is Towards individual-centric emergency management
systems. This edition wishes to highlight the particular needs of the individual
stakeholder in Crisis and Emergency Management and to stimulate discussions that
enable the design of individual-centric crisis and emergency management systems.
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Ahmed Abdeltawab Abdelgawad. (2019). Reliability of expert estimates of cascading failures in Critical Infrastructure. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: Owing to the complexity of Critical Infrastructures and the richness of issues to analyze, numerous approaches are used to model the behavior of CIs. Organizations having homeland security as mission often conduct desktop-based simulations using judgmental assessment of CI interdependencies and cascading failures. Expert estimates concern direct effects between the originally disrupted CI sector and other sectors. To better understand the magnitude of aggregate cascading effects, we developed a system dynamics model that uses expert estimates of cascading failures to compare the aggregate effect of cascading failures with the primary direct cascading failures. We find that the aggregate effect of compounded cascading failures becomes significantly greater than the primary cascading failures the longer the duration of the original disruption becomes. Our conceptually simple system dynamics model could be used to improve desktop-based exercises, since it illustrates consequences that go beyond judgmental assessment.
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Toshihiro Osaragi, & Noriaki Hirokawa. (2019). Simulation Analysis of Fire Hydrant Usability Levels after Large Earthquake. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: Since large earthquakes can disrupt water supply networks, it is essential to gain an understanding of the expected
usability of fire hydrants in post-quake firefighting activities. In this study, data about water supply networks was
collected and a water outage simulation model was constructed in order to predict the likelihood that individual
fire hydrants would become unusable in the wake of a large earthquake. The water outage simulation model was
integrated with a previously developed urban zone damage simulation and a fire department activity simulation
in order to carry out a simulation-based analysis of the 23 wards of Tokyo, after which a quantitative analysis of
the relation-ship between use of fire hydrants and the number of buildings lost to fire was performed. This analysis
revealed the benefits of hardening water lines against earthquakes, fire hydrant usage variations depending on
locality, and the benefits of using water pressure sensors to identify usable fire hydrants.
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Anying Chen, Guofeng Su, & Manchun Liang. (2019). Simulation of Crowd Response During Emergency Considering People's Rational and Irrational Thinking. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: Human beings have been facing numerous emergencies which could threaten their property or even their lives in all ages. In order to learn how people respond to the emergencies like earthquakes and fire disasters, a two-stage simulation considering people?s rational thinking and irrational thinking was conducted. Results show that people?s irrational thinking, like the herd effect, could exaggerate people?s behavior of conformity, and it changes the spatial features that stronger herd effect leads to higher cohesion level. It is also worth mentioning that crowd response of condition of smaller population is harder to predict because of its instability, and the response of the very first part of people who make decisions could make great changes to the whole crowd?s response. These results could give some enlightenment on the evacuation instruction during emergencies and future research works.
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Haya Aldossary, & Graham Coates. (2019). A Preliminary Optimisation-based Approach to Coordinate the Response of Ambulances in Mass Casualty Incidents. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: Mass Casualty Incidents (MCIs) may occur with no notice and require a rapid response to manage the casualties and arrange their transportation to hospitals. MCIs may result in different numbers of casualties and fatalities. Further, response time can play a crucial role in reducing fatalities and protecting lives. This paper reports on a preliminary optimisation-based approach, termed MCIER, which has been developed to co-ordinate the response of ambulances to multiple MCIs. In this approach, a realistic representation of the road network is modelled for the geographical area of interest. Also, a Neighbourhood Search Algorithm (NSA) has been developed in order to find the optimum solution to the problem under consideration. A hypothetical case study of a MCI in Newcastle-upon-Tyne has been considered to investigate the effect on response time of the time of day, and day of week, on which the incident occurs.
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Patrick Lieser, Julian Zobel, Björn Richerzhagen, & Ralf Steinmetz. (2019). Simulation Platform for Unmanned Aerial Systems in Emergency Ad Hoc Networks. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
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Marco Polo Ruiz Herrera, & Juan Sánchez Díaz. (2019). Improving Emergency Response through Business Process, Case Management, and Decision Models. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: The emergency procedures contain a set of actions responsible for providing the necessary corrective measures to address an emergency. The relevance of contextual knowledge during emergency responses is of utmost importance since many decisions are made from the information gathered in real time that sometimes conflicts with the formal knowledge specified in the emergency plan. Consequently, tools that support the emergency plan mentioned must be sensitive to context and allow decision making at the time an emergency takes place. We demonstrate how Case Management Modeling Notation (CMMN) along with Decision Model and Notation (DMN) are very suitable approaches to obtain a flexible model adapted to the context-driven response processes.
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Flavio Dusse, Renato Novais, & Manoel Mendonça. (2019). Understanding the Main Themes Towards a Visual Analytics Based Model for Crisis Management Decision-Making. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: Crisis Management (CM) refers to the ability to deal with crisis tasks in different phases and iterations. People working in a crisis are generally under stress to make the right decision at the right time. They have to process large amounts of data and to assimilate the received information in an intuitive and visual way. Visual Analytics (VA) is potentially useful to analyze and understand the huge amount of data in several areas including in a crisis. We designed a survey protocol to understand which themes influence visualizations to support CM. In previous work, we carried out systematic mapping studies, analysis of official documents, ethnographic studies, questionnaires during the large events held in Brazil in recent years. In this work, we interviewed eight CM specialists. We analyzed this data qualitatively with the coding technique. Then we evaluated the coding results with the focus group technique. With the results, we identified the relationships between the visual needs and other main themes of influence for CM. This thematic synthesis enabled us to build a draft model based on VA.
We hope that, after future cycles of validations and improvements, the agencies that manage crises might use this model as a reference in their activities of knowledge production and decision-making.
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Juan Francisco Carías, Leire Labaka, Jose Maria Sarriegi, Andrea Tapia, & Josune Hernantes. (2019). The Dynamics of Cyber Resilience Management. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: With the latent problem of security breaches, denial of service attacks, other types of cybercrime, and cyber incidents in general, the correct management of cyber resilience in critical infrastructures has become a high priority. However, the very nature of cyber resilience, requires managing variables whose effects are hard to predict, and that could potentially be expensive. This makes the management of cyber resilience in critical infrastructures a substantially hard task.
To address the unpredictability of the variables involved in managing cyber resilience, we have developed a system dynamics model that represents the theoretical behaviors of variables involved in the management of cyber resilience. With this model, we have simulated different scenarios that show how the dynamics of different variables act, and to show how the system would react to different inputs.
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Eric Daudé, Kevin Chapuis, Clément Caron, Alexis Drogoul, Benoit Gaudou, Sebastien Rey-Coyrehourq, et al. (2019). ESCAPE: Exploring by Simulation Cities Awareness on Population Evacuation. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: Partial or total horizontal evacuation of populations in urban areas is an important protection measure against a natural or technological risk. However, casualties during massive displacement in a context of stress and in a potentially degraded environment may be high due to non-compliance with instructions, accidents, traffic jams, incivilities, lack of preparation of civil security or increased exposure to hazards. Working in evacuation plans is therefore fundamental in avoiding casualties caused by improvisation and in promoting self-evacuation whenever possible. Since it is impossible to re-create the conditions of a crisis on the ground to assess such evacuation plans, there is a need for realistic models in order to evaluate them using simulations. In this paper, we present the ESCAPE software framework that helps in the development of such plans and testing them. In particular, ESCAPE, which uses the GAMA open-source platform as a core component, provides an agent-based simulation tool that supports simulation of the evacuation of a city's population at fine temporal and Geographical scales. The framework was developed such that it works for a wide range of scenarios, both in terms of hazards, geographical configurations, individual behaviors and crisis management. In order to show its adaptability, two applications are presented, one concerning the evacuation of the city of Rouen (France) in the context of a technological hazard and the other pertaining to the evacuation of the district of Hanoi (Vietnam) in the event of floods.
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Meshal Alharbi, & Graham Coates. (2019). Assessing Flood Recovery of Small Businesses using Agent-Based Modelling and Simulation. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: In developed countries, small and medium-sized enterprises (SMEs) represent the majority of all businesses, e.g. 99.9% in the UK. Given this significant proportion, any disruption to the operation of SMEs will have a negative impact on a nation?s economy. In the context of flooding, this paper reports on the use of agent-based modelling and simulation (ABMS) to assess SMEs immediate response and short-term recovery. In particular, it focuses on the interactions between manufacturing SMEs and mutual aid partners, and retail SMEs and companies specializing in refurbishing premises. Results show that a manufacturing SME with a mutual aid partner can reduce loss in production by approximately 6% over a 7 working day period. In relation to retail
SMEs, those with employees able to be allocated to refurbish its premises recovered faster than SMEs employing a refurbishment company, potentially one day earlier.
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Xiujuan Zhao, Jianguo Chen, Peng Du, Wei Xu, Ran Liu, & Hongyong Yuan. (2019). Location-allocation model for earthquake shelter solved using MPSO algorithm. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: Constructing shelters in suitable quantities, with adequate capacities and at the right locations is essential for evacuees under earthquake disasters. As one of the disaster management methods, constructing shelters can help to significantly reduce disruption and devastation to affected population. Mathematical models have been used to solve this problem allied with a heuristic optimization algorithm. The optimization of evacuation efficiency, as one of the most important objectives, has many expressive forms, such as minimizing evacuation distance and evacuation time. This paper proposes a new model that aims to minimize evacuation time with a new calculation method and to maximize total evacuees? comfort level. The modified particle swarm optimization (MPSO) algorithm is employed to solve the model and the result is compared with a model that calculated evacuation time differently and a model without distance constraint, respectively.
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Duygu Pamukçu, Christopher William Zobel, & Andrew Arnette. (2019). A New Data-Driven Approach to Measuring Hurricane Risk. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: Improving disaster operations requires understanding and managing risk. This paper proposes a new data-driven approach for measuring the risk associated with a natural hazard, in support of developing more effective approaches for managing disaster operations. The paper focuses, in particular, on the issue of defining the inherent severity of a hazard event, independent of its impacts on human society, and concentrates on hurricanes as a specific type of natural hazard. After proposing a preliminary severity measure in the context of a hurricane, the paper discusses the issues associated with collecting empirical data to support its implementation. The approach is then illustrated by comparing the relative risk associated with two different locations in the state of North Carolina subject to the impacts of Hurricane Florence in 2018.
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Linda Elmhadhbi, Mohamed-Hedi Karray, & Bernard Archimède. (2019). A Modular Ontology for Semantically Enhanced Interoperability in Operational Disaster Response. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: Up to now, the world has witnessed how inadequate communication capabilities can adversely affect disaster response efforts. There are various Emergency Responders (ERs) that potentially must work together towards a successful resolution of the disaster. However, the different terminologies and technical vocabularies that are being exchanged between the ERs may lead to a misunderstanding and lack of semantic integrity. Yet, understanding the semantics of the exchanged data is one of the major challenges. The purpose of this work is to define the complex knowledge of the ERs by proposing a common and modular ontology shared by all the stakeholders so as to come up with a common shared vocabulary in order to ensure semantic interoperability between ERs. In this paper, we present POLARISCO and we discuss how it was developed using Basic Formal Ontology as an upper-level ontology and Common Core Ontology as a mid-level ontology to define each module.
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Sammy Abdelghani Teffali, Nada Mattta, & Eric Chatelet. (2019). Generating Crisis Situation by Using Ontology and Fuzzy Theory. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: A crisis is a complex situation, difficult to manage by the actors. Some of them are under stress it is difficult to
deal with problems when consequences cannot be predict. The human conditions (concerning familial and life)
and, the influence of the environment related to politics, economic, and media pushe the actors to lose control of
the crisis situation. The question we face in this paper is: ?is it possible to use the fuzzy theory for predicting the
stress impact in crisis?? Our main hypothesis to represent experience feedback in a situation prediction in order
to show negative consequences and correctness actions is taken account. Fuzzy theory concept is used in
prediction in order to generate several situations.
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Samer Cheade, Nada Matta, Jean-Baptiste Pothin, & Remi Cogranne. (2019). Situation Representation and Awareness for Rescue Operations. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: During rescue operations, being aware of the situation is very critical for rescuers and decision-makers to reduce the impacts. This work aims to support situation awareness amongst actors participating in rescue operations by adopting an ontology-based approach. An application ontology is proposed based on existing related ontologies and operational expertise collection. It will help to ensure common situation representation and understanding between different actors. After that, a knowledge-based system will be developed and integrated in actors? environment to support decision-making. Our preliminary results are shown in this paper.
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Florian Vandecasteele, Krishna Kumar, Kenzo Milleville, & Steven Verstockt. (2019). Video Summarization And Video Highlight Selection Tools To Facilitate Fire Incident Management. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: This paper reports on the added value of combining different types of sensor data and geographic information for fire incident management. A survey was launched within the Belgian fire community to explore the need of added value and the use of new types of sensor data during a fire incident. This evaluation revealed that people are visually-oriented and that video footages and images are of great value to gain insights in a particular problem. However, due to the limited available time (i.e., fast decisions need to be taken) and the large amount of cameras it is not feasible to analyze all video footages sequentially. To solve this problem we propose a video summarization mechanism and a video highlight selection tool based on the automatic generated image and video tags.
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Denis Barcaroli, Alex Coletti, Antonio De Nicola, Antonio Di Pietro, Luigi La Porta, Maurizio Pollino, et al. (2019). An Automatic Approach to Qualitative Risk Assessment in Metropolitan Areas. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: Risk assessment aims at improving prevention and preparedness phases of the crisis management lifecycle.
Qualitative risk assessment of a system is important for risks identification and analysis by the various stakeholders and often requires multi-disciplinary knowledge. We present an automatic approach to qualitative
risk assessment in metropolitan areas using semantic techniques. In particular, users are provided with a computational support to identify and prioritize by relevance risks of city services, through generation of
semantic descriptions of risk situations. This approach is enabled by a software system consisting of: TERMINUS, a domain ontology representing city knowledge; WS-CREAM, a web service implementing risk identification and ranking functions; and CIPCast, a GIS-based Decision Support System with functions of risk
forecast due to natural hazards. Finally we present the results of a preliminary validation of the generated risks concerning some points of interest in two different areas of the city of Rome.
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Joao Moreira, Luis Ferreira Pires, & Marten Sinderen. (2019). SEMIoTICS: Semantic Model-Driven Development for IoT Interoperability of Emergency Services. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: Modern early warning systems (EWSs) use Internet-of-Things (IoT) technologies to realize real-time data acquisition, risk detection and message brokering between data sources and warnings? destinations. Interoperability is crucial for effective EWSs, enabling the integration of components and the interworking with other EWSs. IoT technologies potentially improve the EWS efficiency and effectiveness, but this potential can only be exploited if interoperability challenges are properly addressed. The three main challenges for interoperability are: (1) achieving semantic integration of a variety of data sources and different representations; (2) supporting time- and safety-critical applications with performance and scalability; and (3) providing data analysis for effective responses with personalized information requirements. In this paper, we describe the ?SEmantic Model-driven development for IoT Interoperability of emergenCy serviceS? (SEMIoTICS) framework, which supports the development of semantic interoperable IoT EWSs. The framework has been validated with a pilot performed with accident use cases at the port of Valencia. The validation results show that it fulfils the requirements that we derived from the challenges above.
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Basanta Chaulagain, Aman Shakya, Bhuwan Bhatt, Dip Kiran Pradhan Newar, Sanjeeb Prasad Panday, & Rom Kant Pandey. (2019). Casualty Information Extraction and Analysis from News. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: During unforeseen situations of crisis such as disasters and accidents we usually have to rely on local news reports for the latest updates on casualties. The information in such feeds is in unstructured text format, however, structured data is required for analysis and visualization. This paper presents a system for automatic extraction and visualization of casualty information from news articles. A prototype online system has been implemented and tested with local news feed of road accidents. The system extracts information regarding number of deaths, injuries, date, location, and vehicles involved using techniques like Named Entity Recognition, Semantic Role Labeling and Regular expressions. The entities were manually annotated and compared with the results obtained from the system. Initial results are promising with good accuracy overall. Moreover, the system maintains an online database of casualties and provides information visualization and filtering interfaces for analysis.
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Prithviraj Dasgupta, & Deepak Khazanchi. (2019). A Unified Approach Integrating Human Shared Mental Models with Intelligent Autonomous Team Formation for Crisis Management. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: Autonomous systems are being exceedingly used to assist humans in various crisis responses scenarios such as earthquakes and nuclear disasters. Because they operate in highly unstructured and uncertain environments, failures are an inherent part of such autonomous systems, and, techniques for making these systems robust to failures arising from computer hardware, software or communication malfunctions are already integrated into their design. However, an important aspect while designing such systems is often times overlooked: how to better coordinate and communicate across distributed, possibly diverse human teams who are working in cooperation with autonomous systems into the design of the autonomous system itself. Unfortunately, this results in limited adoption of autonomous systems in real-life crisis scenarios. In this working paper, we describe ongoing work that attempts to address this deficit by integrating research on shared mental models between humans with techniques for autonomous agent team formation in the context of search and rescue scenarios.
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Jennifer Lisa Chan, Gabriel Nam, Allison G. Marshall, & Hemant Purohit. (2019). Trends in Humanitarian Health Information during 2010 Haiti Earthquake: Motivation for Curating Domain Knowledge Base. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: Health response plays a major role during disasters and information management plays a crucial role in situational awareness to adapt to evolving needs. Health organizations exchange information often through narrative-based documents called situation reports. Although situation reports are widely shared, they are an increasingly challenging information source from which to infer knowledge for situational awareness. This paper analyzed health information from traditional health reports using mixed methods during the aftermath of the 2010 Haiti Earthquake and provides insights into the patterns of what?s being said, how it?s being said, and trends over time. Opportunities lie ahead to analyze narrative documents at scale by combining human knowledge from qualitative coding with machine intelligence. In addition, developing unifying health domain ontologies representing diverse humanitarian health concepts will advance computational techniques to improve
the efficiency and accuracy of retrieving knowledge for improved situational awareness and potential decision
making during humanitarian health response.
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David Paulus, Kenny Meesters, Gerdien de Vries, & Bartel Van de Walle. (2019). The reciprocity of data integration in disaster risk analysis. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: Humanitarian organizations are increasingly challenged by the amount of data available to drive their decisions. Useful data can come from many sources, exists in different formats, and merging it into a basis for analysis and planning often exceeds organizations? capacities and resources. At the same time, affected communities? participation in decision making processes is often hindered by a lack of information and data literacy capacities within the communities. We describe a participatory disaster risk analysis project in the central Philippines where the community and a humanitarian NGO worked towards a joint understanding of disaster risks and coping capacities through data integration and IT-supported analysis. We present findings from workshops, focus group discussions and semi-structured interviews, showing the reciprocal effects of the collaborative work. While the community valued the systematically gathered and structured evidence that supported their own risk perceptions and advocacy efforts, the humanitarian NGO revisited established work practices for data collection for analysis and planning.
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Olawunmi George, Rizwana Rizia, MD Fitrat Hossain, Nadiyah Johnson, Carla Echeveste, Jose Lizarraga Mazaba, et al. (2019). Visualizing Early Warning Signs of Behavioral Crisis in Military Veterans: Empowering Peer Decision Support. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: Several attempts have been made at creating mobile solutions for patients with mental disorders. A preemptive approach would definitely outdo a reactive one. This project seeks to ensure better crisis detection, by assigning patients (veterans) to caregivers (mentors). This is called the mentor-mentee approach. Enhanced with the use of mobile technology, veterans can stay connected in their daily lives to mentors, who have gone through the same traumatic experiences and have overcome them. A mobile application for communication between veterans and their mentors has been developed, which helps mentors get constant feedback from their mentees about their state of well-being. However, being able to make good deductions from the data given as feedback is of great importance. Under-represent ing or over-representing the data could be dangerously misleading. This paper presents the design process in this project and the key things to note when designing a data visualization for
timely crisis detection and decision-making.
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Kenny Meesters, Vittorio Nespeca, & Tina Comes. (2019). Designing Disaster Information Management Systems 2.0: Connecting communities and responders. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: Information and supporting information systems is a key element in an effective emergency response. From
creating situational awareness to informed decision making, information enables responders to optimize their
decisions and operations. Today, with the increased availability of information technology around the globe, a
new active player in the field of information management is emerging as communities are becoming increasingly
active in the field of information gathering, analyzing and sharing.
However, communities may have specific requirements and approaches to using information systems in crisis
situations. Moreover, connecting information systems between communities and responder pose specific
challenges due to the different information needs, capacities and incentives to use them. In this paper we build on
the DERMIS premises and explore through a case study if and how these principles apply to inclusive information
systems. We present the initial findings of this work of designing information systems involving both communities
and formal responders.
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