Abstract: Recent development in disaster management and humanitarian aid is shaped by the rise of new information sources such as social media or volunteered geographic information. As these show great potential, making sense out of the new geographical datasets is a field of important scientific research. Therefore, this paper attempts to develop a typology of geographical information crowdsourcing. Furthermore, we use this typology to frame existing crowdsourcing projects and to further point out the potential of different kinds of crowdsourcing for disaster management and humanitarian aid. In order to exemplify its practical usage and value, we apply the typology to analyze the crowdsourcing methods utilized by the members of the Missing Maps project developed in South Kivu.

Abstract: In 2014 a small fire started in a forest in central Sweden. Within a few days it developed into the largest wildfire in Sweden in the last 50 years. As the scale of the fire increased, so did the need for direction and coordination of the resources engaged in the response operation. Both official investigators and the research community have studied the challenges and come up with recommendations for improvements of the Swedish crisis management system. All authors of this paper have been involved in such efforts. This paper is a result of us trying to formulate lessons learnt based on several written reports and official discussions. The development of the narratives constructed by individuals involved in the response, investigators and researchers is analyzed. We conclude that researchers need to pay attention to their own role in this development. Maybe there is a need for a game changer on the methodological side?

Abstract: Breakdowns in team cognition are accepted as an explanation for system collapses, especially in complex environments. In the nuclear industry, training for system collapses is a part of the job for control room teams. Such training focus both on improving skills required for recognising and solving disturbances and on improving team processes. This paper presents an approach to team training for nuclear power plant control room teams with the purpose of making the system more resilient by improving debriefing sessions through feedback on shared strategic understanding among team members.

Abstract: Emergency situations are characterized by their complexity and the heterogeneity of the available information. Emergency managers are frequently confronted with redundant or irrelevant information, causing the problem of information overload. Evidence of this problem was identified in an exploratory survey conducted in the Center for Integrated Command and Control of Rio de Janeiro (CICC-RJ). In this paper, we present a conceptual architecture that allows a user to handle this influx of information. From a set of available data, a manager can select those of interest, which can then be transformed and mapped into one or more views, and organized in a dashboard. The whole process is interactive, allowing the manager to redefine his/her dashboard as needed. In addition, we provide collaborative mechanisms, given that, at times, it is not possible for a single user to handle such large datasets alone.

Abstract: This paper presents preliminary analysis from a validation study of a novel emergency medicine command and control training and evaluation simulator: DIGEMERGO®. The simulated emergency scenario was a surge capacity event at a generic emergency department, in which the participants took on a management role as the emergency department?s coordinating head nurse. A between group validation design with medical expert and novice participants was used. Initial analysis examined three triage measures associated with surge capacity management performance: time to triage, amount of patients triaged, and triage accuracy. The results show that experts were significantly more accurate at triaging in-hospital patients, but not incoming trauma patients. No significant differences in time or number of patients triaged was found. These initial results partially indicate simulator validity, but trauma patient triage accuracy suffered from a confounding variable in the triage system used. Analysis of additional measures is undergoing to further investigate validity claims.

Abstract: When Hurricane Sandy swept over the US eastern seaboard in October 2012, it was the most tweeted about event at the time. However, some of the most affected areas were underrepresented in the social media conversation about Sandy. Here, we examine the hurricane-related experiences and behaviors shared on Twitter by residents of Far Rockaway, a New York City neighborhood that is geographically and socioeconomically vulnerable to disasters, which was significantly affected by the storm. By carefully filtering the vast Twitter data, we focus on 41 Far Rockaway residents who offer rich personal accounts of their experience with Sandy. Analyzing their first-person narratives, we see risk perception and protective decision-making behavior in their data. We also find themes of invisibility and neglect when residents expressed feeling abandoned by the media, the city government, and the overall relief efforts in the aftermath of Sandy.

Abstract: Large-scale crisis events require coordination between the many responding stakeholders to provide timely, relevant, and accurate information to the affected public. In this paper, we examine how social media can support these coordinated public information efforts. This research considers how emergency responders mentioned different organizations, institutions, and individuals by examining the social media communications of police and fire departments during Hurricane Sandy. We find that these departments use mentions to reference other sources of information, recommend credible information and sources, and rebroadcast information. These mentions offer insight into how emergency responders fit within a broader crisis information network and the types of entities that responders trust and recommend to provide information to the public.

Abstract: The recovery of small businesses from a disaster is critical to community recovery. Such businesses can be extremely vulnerable to disasters, particularly because they often occupy a single location and have a localized customer base. Although social media is an effective platform for information dissemination, and has been extensively used in a disaster context, the way in which small businesses use social media in this context, and the effectiveness of those efforts, are still not well understood. With this in mind, this paper uses the 2013 floods along the Front Range in Colorado as a case study to help improve our understanding of how small businesses use social media in disaster situations. Characterizing the organizations' behavior involves using both qualitative and quantitative approaches, and the paper focuses on an initial qualitative analysis.

Abstract: Radiation measurements are key information in post-nuclear accident situations. Automated Twitter accounts have been used to share the readings, but often in an incomplete way from the perspective of data sharing and risk communication between citizen and radiation experts. In this paper, we investigate the requirements for radiation measurements completeness, by analyzing the perceived usefulness of several metadata items that may go along the measurement itself. We carried out a benchmark of existing uses, and conducted a survey with both experts and lay citizens. We thus produced a set of guidelines regarding the metadata that should be used, and the way to publish it.

Abstract: Rapid crisis response requires real-time analysis of messages. After a disaster happens, volunteers attempt to classify tweets to determine needs, e.g., supplies, infrastructure damage, etc. Given labeled data, supervised machine learning can help classify these messages. Scarcity of labeled data causes poor performance in machine training. Can we reuse old tweets to train classifiers? How can we choose labeled tweets for training? Specifically, we study the usefulness of labeled data of past events. Do labeled tweets in different language help? We observe the performance of our classifiers trained using different combinations of training sets obtained from past disasters. We perform extensive experimentation on real crisis datasets and show that the past labels are useful when both source and target events are of the same type (e.g. both earthquakes). For similar languages (e.g., Italian and Spanish), cross-language domain adaptation was useful, however, when for different languages (e.g., Italian and English), the performance decreased.

Abstract: Social media are now widely used by affected members of the public during an emergency. As these platforms have become mainstream, governments have responded to the public?s expectation that information is available online, particularly during disasters. Emergency management organizations (EMOs) now widely use social media to communicate with the public alongside occasional intelligence gathering. While EMOs increasingly use social media, breakdowns in internal communication can inhibit the dissemination of timely information to their online followers. Drawing on a two-year ethnography at the Queensland Fire and Emergency Services (QFES), an Australian EMO, this paper outlines how the organization uses social media to disseminate information during emergencies and identifies the internal tensions around its use. These tensions include the prioritization of operational duties over public information responsibilities, and the difficulties around requesting and receiving information from operational personnel located on the ground.

Abstract: Conceptual frameworks which seek to integrate social media uses into disaster management strategies are employed in a range of events. With continued variations to social media practices, developments in technology, and changes in online behaviors, it is imperative to provide conceptual frameworks which are relevant, current and insightful. This paper conceptualizes a range of recent literature through an inductive methodology, and presents the themes of Web accessibility and online information reliability as broad and emerging considerations for the identification of social media uses during disasters. It presents a new conceptual framework of current social media uses which may be used to supplement existing frameworks. The framework has been applied to a dataset of Tweets from the 2015 Nepal earthquake to demonstrate its validity. Suggestions for future applications are discussed.