Abstract: Disaster risk management practitioners have the responsibility to make decisions at every phase of the disaster risk management cycle: mitigation, preparedness, response and recovery. The decisions they make affect human life. In this paper, we consider the current state of the use of AI in information extraction (IE) for disaster risk management (DRM), which makes it possible to leverage disaster information in social media. We consolidate the challenges and concerns of using AI for DRM into three main areas: limitations of DRM data, limitations of AI modeling and DRM domain-specific concerns, i.e., bias, privacy and security, transparency and accountability, and hype and inflated expectations. Then, we present a systematic discussion of how explainable AI (XAI) can address the challenges and concerns of using AI for IE in DRM.

Abstract: Taxonomies are integral to systems engineering, as they structure our knowledge of a field and so provide the
foundation for technological development. We contribute such taxonomies for the field of Community
Interaction and Engagement in Crisis and Disaster Management, which represents the interface between
members of the public who commit to relief efforts and established organisations that have a pre-defined role in
crisis management. These actors are unified in their purpose to help those in need, but also set apart by their
organisational structures and modes of operation. We classify the actors of Community Interaction and
Engagement, as well as the interactions between them. Our contribution outlines areas where the application of
Information and Communication Technology can offer benefits to Community Interaction and Engagement.

Abstract: Critical energy infrastructures are more and more focused upon by politics and society. Modern society depends on these structures, since they enable the steady support of electricity and other types of energy. Deliberately precipitated hazards of certain critical parts of electrical transmission systems (ETS) can lead to catastrophic consequences. Therefore, the analysis of feasible security hazards and resulting consequences for the operation of transmission systems are a concern to transmission system operators (TSO). Alas, there is no common method available that comprehensively identifies these feasible security related scenarios and classifies them according to their overall criticality for the safe operation of the ETS. To tackle this challenge, we propose a comprehensive, yet easy-to-apply method to systematically identify and assess the criticality of security threat scenarios. It is conducted in four steps and consists of a matrix based consistency check of threat scenarios in a defined solution space and a convenient semi-quantitative assessment of a risk factor for the ETS. The approach is illustrated by the simplified generic example of an EETS.

Abstract: We investigate an approach that allows exercise managers to design simulations with an explicit focus on building skills, rather than having to focus on all the objects and interactions that a simulation must have. Exercise managers may design exercises at various levels of abstraction and always independently of how those sessions are implemented in simulations, while simulation components that implement the design are assembled and to some extent, automatically, behind the scenes. We outline (1) how Answer Set Programming can assist exercise managers in exercise planning and (2) how automated stage and content generation may be used to invoke appropriate simulation components to realize the design. For deliberate and recurrent training of decision-making skills, stages and content must vary to avoid familiarity (testing effects). We conclude by distilling a main research hypothesis that stipulates how (1) and (2) represent two modes of automated reasoning (so-called deductive versus abductive) and how that distinction clarifies the planning task.

Abstract: The extensive use of social media platforms, especially during disasters, creates unique opportunities for humanitarian organizations to gain situational awareness and launch relief operations accordingly. In addition to the textual content, people post overwhelming amounts of imagery data on social networks within minutes of a disaster hit. Studies point to the importance of this online imagery content for emergency response. Despite recent advances in the computer vision field, automatic processing of the crisis-related social media imagery data remains a challenging task. It is because a majority of which consists of redundant and irrelevant content. In this paper, we present an image processing pipeline that comprises de-duplication and relevancy filtering mechanisms to collect and filter social media image content in real-time during a crisis event. Results obtained from extensive experiments on real-world crisis datasets demonstrate the significance of the proposed pipeline for optimal utilization of both human and machine computing resources.

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.

Abstract: First responders (FRs) in Europe are currently facing large natural and man-made disasters (e.g. wild fire, terrorist attacks, industrial incidents, big floods, gas leaks etc.), that put their own lives and those of thousands of others at risk. Adapted situation awareneSS tools and taIlored training curricula for increaSing capabiliTies and enhANcing the proteCtion of first respondErs (ASSISTANCE) is an ongoing European H2020 project which main objective is to increase FRs Situation Awareness (SA) for helping and protecting different kinds of FRs' organizations that work together in large scale disasters mitigation. ASSISTANCE will enhance the SA of the FRs organisations during their mitigation activities through the integration of new paradigms, tools and technologies (e.g. drones/robots equipped with a range of sensors, robust communications capabilities, etc.) with the main objective of increasing both their protection and their efficiency.

Abstract: The public sector, including state and local government, public health, and emergency management; the private sector; and the Federal Government jointly face challenges with rapidly collecting and validating credentials for individuals applying for employment or volunteering for emergencies, vetting security clearances, and ascertaining suitability. In 2017, for instance, credentialing gaps delayed employees and volunteers from contributing much-needed skills in disaster areas during one of the worst hurricane and wildfire seasons on record while Federal agencies inadvertently issued interim clearances to individuals with criminal records. We propose a secure, modern, mission-capable information technology solution to these with the United States Postal Service hosting this streamlined process by serving as the hub for collection, validation, and transfer of pertinent data. The solution would introduce access points in over 5,000 communities for citizens participating in disaster support operations, as well as those requiring credentialing for employment as part of day-to-day operations.

Abstract: Geographic Information Systems (GIS) have often been poorly considered, planned and implemented across New Zealand's emergency management sector. GIS practitioners involved in emergency management events are often the ones who suffer the consequences of this. Recent significant events have reinforced both the need for a nation-wide coordinated, planned and pro-active approach to implementing GIS for emergency management, and the advantages that GIS can offer to the emergency management sector if implemented properly. This paper offers insights into the “grass roots” foundation of a community called New Zealand GIS for Emergency Management (NZGIS4EM) to address these issues. In its founding year (2017/2018) the priority for an interim NZGIS4EM committee has been to establish the foundation of the community, this is primarily administrative projects. Several other subject targeted projects are also underway or planned relating to data, standards, symbology, common operating picture and interoperability. Key challenges for NZGIS4EM relate to a shortage of funding, logistics of physical meetings, current lack of governance and a lack of legal mandate in New Zealand to enforce standards for emergency management. Attention in the sector is now moving towards the implementation of a Common Operating (or Operational) Picture (COP). Key messages that the author believes are pertinent include: that it's not all about the tools; plan big, but then prioritise and implement small; ensure the COP is used BAU; minimal or no training should be required; ensure it is quicker for frontline users; ensure there is a plan B and a plan C if the internet and/or power goes out; identify and lobby agencies who should be the authoritative source of truth for essential data; implement phases of response for information requirements; consider national and/or regional hosting of platforms, and; recognize that real-time crowd sourced data may be the future of intelligence and plan for that.

Abstract: We estimate the causal effect of the Indian Ocean tsunami in Sri Lanka on household income and consumption eight years after the event, using a quasi-experimental method. A strong association between area-wide tsunami disaster shock and increases in household income and consumption in the long-term emerged from our empirical investigation. Deviating from the common observation on short-term impacts, these results are suggestive of an optimistic potential for some long-lasting potentially successful recovery scenarios. Still, Sri Lanka received a very large amount of external transfers post-tsunami, much larger than is typical for disaster events and one which may not be replicable in other cases. Our findings suggest a more nuanced picture with respect to household consumption impacts. We observe a reduction of food consumption and only find an increase in non-food consumption. The increase in non-food consumption is much smaller than the observed increase in income. We also find that households in high-income regions experienced much better recovery from the disaster. Keywords Sri Lanka, Tsunami, disaster, household survey, long-run impact

Abstract: In complex emergencies, civil and military organizations often find themselves being partners in an international effort aimed at peace keeping, humanitarian relief, and development support. Civil and military partners need to exchange information and to cooperate as required. This assumes effective and efficient Civil-Military Interaction (CMI). However, CMI research literature shows that, in practice, this is far from a reality. In particular, our research indicates that deficiencies in knowledge processes and knowledge management within international civil and military organizations contribute to the causes of ineffective and inefficient CMI. Our research aims to investigate the feasibility of developing technical solutions exploiting knowledge engineering, to support fieldworkers in overcoming these CMI problems. As a first step, this paper introduces a Conceptual Framework (CF) that captures reference models of the CMI domain. The CF has been developed to analyze CMI problems and underlying KM deficiencies. It is being illustrated, explored and validated using real-world case studies.

Abstract: With the advancement and proliferation of technology, non-profit organisations have embraced social media platforms to improve their operational capabilities through brand advocacy, among many other strategies. The effect of such social media campaigns on these institutions, however, remains largely underexplored, especially during disaster periods. This work introduces and applies a quantitative investigative framework to understand how social media influence the behaviour of donors and their usage of these platforms throughout (natural) disasters. More specifically, we explore how on-line engagement – as captured by Facebook interactions and Google search trends – corresponds to the donors’ behaviour during the catastrophic 2019–2020 Australian bushfire season. To discover this relationship, we analyse the record of donations made to the Australian Red Cross throughout this period. Our exploratory study reveals that social media campaigns are effective in encouraging on-line donations made via a dedicated website. We also compare this mode of giving to more regular, direct deposit gifting.