Aladdin Shamoug, Stephen Cranefield, & Grant Dick. (2018). Information Retrieval for Humanitarian Crises via a Semantically Classified Word Embedding. In Kristin Stock, & Deborah Bunker (Eds.), Proceedings of ISCRAM Asia Pacific 2018: Innovating for Resilience – 1st International Conference on Information Systems for Crisis Response and Management Asia Pacific. (pp. 132–144). Albany, Auckland, New Zealand: Massey Univeristy.
Abstract: Decision-makers in humanitarian crisis need information to guide them in making critical decisions. Finding information in such environments is a challenging task. Therefore, decision-makers rely on domain experts who possess experience and knowledge from previous humanitarian crises to provide them with the information they need. In this paper, we explore the ability of the existing computing technologies to augment the capabilities of those experts and help decision-makers to make faster and better decisions. Among many computing technologies we have today, word embedding and the semantic web are able to support such augmentation of the domain expert. In this paper, we train a word embedding model using word2vec, transform words and terms from news archive to entities in domain ontology, annotate those entities with their equivalent concepts from upper ontologies, and reason about them using semantic similarity and semantic matching, to represent and retrieve knowledge, and answer questions of interest to decision-makers in humanitarian crises. The approach was evaluated by comparing the use of word embeddings with and without semantic classification for the retrieval of information about the current humanitarian crisis in Syria.
|
Naveen Ashish, & Sharad Mehrotra. (2010). Community driven data integration for emergency response. In C. Zobel B. T. S. French (Ed.), ISCRAM 2010 – 7th International Conference on Information Systems for Crisis Response and Management: Defining Crisis Management 3.0, Proceedings. Seattle, WA: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: This paper describes our work in progress on an approach and technology for providing integrated data access in situational awareness applications – particularly for disaster and emergency response. The key new aspect of our work is an approach where information aggregation, processing, and integration capabilities are offered as a service to any new application builder. Further, we provide a framework for possibly reusing prior information integration knowledge, the development of which demands the major fraction of time and complexity in a new application, in a customized fashion for new application. Our overall goal is to provide a framework where integrated access to critical data in an emergency response situation can be enabled very rapidly and by personnel with basic IT and data handling expertise. Our approach, while general purpose, is currently motivated by and grounded in the context of situational awareness systems for incident commander decision support in the fire response domain.
|
Peter Berggren, Björn J.E. Johansson, Nicoletta Baroutsi, Isabelle Turcotte, & Sébastien Tremblay. (2014). Assessing team focused behaviors in emergency response teams using the shared priorities measure. In and P.C. Shih. L. Plotnick M. S. P. S.R. Hiltz (Ed.), ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management (pp. 130–134). University Park, PA: The Pennsylvania State University.
Abstract: The purpose of this work in progress paper is to report on the method development of the Shared Priorities measure to include content analysis, as a way of gaining a deeper understanding of team work in crisis/emergency response. An experiment is reported where the performance of six trained teams is compared with the performance of six non-trained teams. The experiment was performed using an emergency response microworld simulation with a forest fire scenario. Dependent measures were simulation performance, the Crew Awareness Rating Scale (CARS), and content analysis. Trained teams performed better and scored higher on measures of team behaviors.
|
Nong Chen, & Ajantha Dahanayake. (2006). Personalized situation aware information retrieval and access for crisis response. In M. T. B. Van de Walle (Ed.), Proceedings of ISCRAM 2006 – 3rd International Conference on Information Systems for Crisis Response and Management (pp. 214–222). Newark, NJ: Royal Flemish Academy of Belgium.
Abstract: Crisis response is an information intensive process, which produces or consumes large quantities of information from different relief organizations. Although personalized information retrieval and access has been realized as an efficient means to accelerate information acquisitions, most IT enabled applications in the fields can only provide uniform information to all the involved relief organizations. The traditional centralized design principle dominantly used to address the inter-organizational information accesses over boundaries is no longer feasible due to its lack of flexibility and adaptability to deal with dynamically changing information needs caused by the unpredictable nature of the crises. In this paper we present our ongoing research regarding a plug and play service architecture for personalized, situation aware information retrieval and access services, which offers a new way of thinking about the retrieval of personalized information in the context of crisis response.
|
Dirk Fahland, Timo Mika Gläßer, Bastian Quilitz, Stephan Weißleder, & Ulf Leser. (2007). HUODINI-flexible information integration for disaster management. In K. Nieuwenhuis P. B. B. Van de Walle (Ed.), Intelligent Human Computer Systems for Crisis Response and Management, ISCRAM 2007 Academic Proceedings Papers (pp. 255–262). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Fast and effective disaster management requires access to a multitude of heterogeneous, distributed, and quickly changing data sets, such as maps, satellite images, or governmental databases. In the last years, also the information created by affected persons on web sites such as flickr.com or blogger.com became an important and very quickly adapting source of information. We developed HUODINI, a prototype system for the flexible integration and visu-alization of heterogeneous data sources for disaster management. HUODINI is based on Semantic Web technologies, and in particular RDF, to offer maximal flexibility in the types of data sources it can integrate. It supports a hybrid push/pull approach to cater for the requirements of fast-changing sources, such as news feeds, and maximum performance for querying the integrated data set. In this paper, we describe the design goals underlying our approach, its architecture, and report on first experiences with the system.
|
Qing Gu, & David Mendonça. (2005). Patterns of group information-seeking in a simulated emergency response environment. In B. C. B. Van de Walle (Ed.), Proceedings of ISCRAM 2005 – 2nd International Conference on Information Systems for Crisis Response and Management (pp. 109–116). Brussels: Royal Flemish Academy of Belgium.
Abstract: Groups in emergency response environment may be confronted with problems that cannot be solved by following predefined procedures. They must therefore engage in a collective search for relevant information, cooperating and collaborating as they move towards the deadline. Information technologies and expertise may help shape group information seeking and determine its effectiveness. By understanding how response personnel search for information in emergencies and extending the findings to determine demands on information systems, we may begin to understand how to support and train for skillful information seeking in emergency situations. Accordingly, this research evaluates the impact of decision support systems and member expertise on group information-seeking behavior in a simulated emergency response environment. The results of the evaluation are then used to identify how information technologies may further support information seeking in emergency response.
|
Imen Bizid, Patrice Boursier, Jacques Morcos, & Sami Faiz. (2015). A Classification Model for the Identification of Prominent Microblogs Users during a Disaster. In L. Palen, M. Buscher, T. Comes, & A. Hughes (Eds.), ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management. Kristiansand, Norway: University of Agder (UiA).
Abstract: Content shared in microblogs during disasters is expressed in various formats and languages. This diversity makes the information retrieval process more complex and computationally infeasible in real time. To address this, we propose a classification model for the identification of prominent users who are sharing relevant and exclusive information during the disaster. Users who have shared at least one tweet about the disaster are modeled using three kinds of time-sensitive features, including topical, social and geographical features. Then, these users are classified into two classes using a linear Support Vector Machine (SVM) to evaluate them over the extracted features and identify the most prominent ones. The first results using the actual dataset, show that our model has a high accuracy by detecting most of the prominent users. Moreover, we demonstrate that all the proposed features used by our model are indispensable to achieve this high accuracy.
|
Muhammad Imran, Shady Elbassuoni, Carlos Castillo, Fernando Díaz, & Patrick Meier. (2013). Extracting information nuggets from disaster- Related messages in social media. In J. Geldermann and T. Müller S. Fortier F. F. T. Comes (Ed.), ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management (pp. 791–801). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Microblogging sites such as Twitter can play a vital role in spreading information during “natural” or man-made disasters. But the volume and velocity of tweets posted during crises today tend to be extremely high, making it hard for disaster-affected communities and professional emergency responders to process the information in a timely manner. Furthermore, posts tend to vary highly in terms of their subjects and usefulness; from messages that are entirely off-topic or personal in nature, to messages containing critical information that augments situational awareness. Finding actionable information can accelerate disaster response and alleviate both property and human losses. In this paper, we describe automatic methods for extracting information from microblog posts. Specifically, we focus on extracting valuable “information nuggets”, brief, self-contained information items relevant to disaster response. Our methods leverage machine learning methods for classifying posts and information extraction. Our results, validated over one large disaster-related dataset, reveal that a careful design can yield an effective system, paving the way for more sophisticated data analysis and visualization systems.
|
Julien Coche, Aurelie Montarnal, Andrea Tapia, & Frederick Benaben. (2020). Automatic Information Retrieval from Tweets: A Semantic Clustering Approach. In Amanda Hughes, Fiona McNeill, & Christopher W. Zobel (Eds.), ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management (pp. 134–141). Blacksburg, VA (USA): Virginia Tech.
Abstract: Much has been said about the value of social media messages for emergency services. The new uses related to these platforms bring users to share information, otherwise unknown in crisis events. Thus, many studies have been performed in order to identify tweets relating to a crisis event or to classify these tweets according to certain categories. However, determining the relevant information contained in the messages collected remains the responsibility of the emergency services. In this article, we introduce the issue of classifying the information contained in the messages. To do so, we use classes such as those used by the operators in the call centers. Particularly we show that this problem is related to named entities recognition on tweets. We then explain that a semi-supervised approach might be beneficial, as the volume of data to perform this task is low. In a second part, we present some of the challenges raised by this problematic and different ways to answer it. Finally, we explore one of them and its possible outcomes.
|
Benedikt Ley, Volkmar Pipek, Tim Siebigteroth, & Torben Wiedenhöefer. (2013). Retrieving and exchanging of information in inter- Organizational crisis management. In J. Geldermann and T. Müller S. Fortier F. F. T. Comes (Ed.), ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management (pp. 812–822). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Information is the most valuable resource for coping and recovery work in crisis management. It is the foundation for coordination, collaboration and decision-making. However, several challenges face information retrieval, evaluation and exchange processes in inter-organizational crisis management. On the one hand, due to the dynamic nature of crisis situations, information demands are hardly predictable and change in the course of time. Moreover, inter-organizational issues like terminology issues, policy constrains or even the lack of awareness about information available are influencing factors and need to be considered in designing appropriate ICT. In this paper we report from an empirical study, where we had a closer look on information retrieval and exchange practices in scenarios of medium to large power outages in Germany on an interorganizational level. Derived from these results, we were able to present a reference implementation of an interorganizational information repository (IOIR) and report our findings from a related evaluation.
|
Eli Rohn, & Gil Erez. (2012). Fighting agro-terrorism in cyberspace: A framework for intention detection using overt electronic data sources. In Z.Franco J. R. L. Rothkrantz (Ed.), ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management. Vancouver, BC: Simon Fraser University.
Abstract: Agro Terrorism is “a hostile attack, towards an agricultural environment, including infrastructures and processes, in order to significantly damage national and international political interests”. This special session within the early warning track is aimed at reducing agro-terrorism related risks by either means of prevention (intelligence gathering using data mining and chatter mining, for example) or means to response to such an attack by early detection of exotic/foreign pathogenic agents, early prediction of disease dispersion patterns, implementation of biosecurity measures, and the development of future methodologies and techniques related to food defense and post-event response. This paper focuses on intention detection using overt data sources on the World Wide Web as they relate to agro-terrorism threats. The paper focuses on early detection that can lead to prevention of such acts, yet a variety of the techniques presented here are also useful for helping in post-event perpetrators detection. © 2012 ISCRAM.
|
Jorge H. Roman, Linn Marks Collins, Ketan K. Mane, Mark L.B. Martinez, Carolyn E Dunford, & James E. Powell Jr. (2008). Reducing information overload in emergencies by detecting themes in web content. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 101–107). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Information on the Web has become increasingly important in disaster response. Yet much of this information is redundant. We are creating a suite of electronic knowledge management (eKM) tools that can be used to reduce by an order of magnitude the information that people need to read in order to gain and maintain awareness of web content during emergencies. In this paper, we describe research-in-progress on developing these tools and applying them to web content from organizations' websites and individuals' blogs. Results so far indicate that organizations' websites and individuals' blogs provide redundant coverage of general issues and that each provides additional information about specific issues. By using the tools we are developing, responders and victims will be able to quickly gather an overview of general issues derived from many websites, then learn more about specific issues by navigating to a few websites.
|
Teun Terpstra, Richard Stronkman, Arnout De Vries, & Geerte L. Paradies. (2012). Towards a realtime Twitter analysis during crises for operational crisis management. In Z.Franco J. R. L. Rothkrantz (Ed.), ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management. Vancouver, BC: Simon Fraser University.
Abstract: Today's crises attract great attention on social media, from local and distant citizens as well as from news media. This study investigates the possibilities of real-time and automated analysis of Twitter messages during crises. The analysis was performed through application of an information extraction tool to nearly 97,000 tweets that were published shortly before, during and after a storm hit the Pukkelpop 2011 festival in Belgium. As soon as the storm hit the festival tweet activity increased exponentially, peaking at 576 tweets per minute. The extraction tool enabled analyzing tweets through predefined (geo)graphical displays, message content filters (damage, casualties) and tweet type filters (e.g., retweets). Important topics that emerged were 'early warning tweets', 'rumors' and the 'self-organization of disaster relief' on Twitter. Results indicate that automated filtering of information provides valuable information for operational response and crisis communication. Steps for further research are discussed. © 2012 ISCRAM.
|
Sébastien Tremblay, Peter Berggren, Martin Holmberg, Rego Granlund, Marie-Eve Jobidon, & Paddy Turner. (2012). A multiteam international simulation of joint operations in crisis response. In Z.Franco J. R. L. Rothkrantz (Ed.), ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management. Vancouver, BC: Simon Fraser University.
Abstract: Concepts such as trust, shared understanding, cultural differences, mental workload, and organizational structure all impact upon the effectiveness of an organization (e.g., Tindale & Kameda, 2000), and even more so in the context of large scale multinational operations (e.g, Smith, Granlund, & Lindgen, 2010). In order to study these concepts we plan a multinational, distributed experiment with participants from three nations collaborating in the same virtual environment: Canadian, British, and Swedish participants will work together as part of a multinational MTS to deal with a complex task and gain control of a crisis situation. Empirical research on MTS remains limited (see, e.g., DeChurch & Marks, 2006) particularly at the multinational level where the investigation of MTS has been so far focused on case studies and exercises (e.g., Goodwin, Essens, & Smith, 2012). Therefore, there is a need to empirically study multinational MTS in order to assess the specific issues that multinational operations face, notably cultural and languages differences. The simulation environment used as experimental platform for this project is C3Fire (www.c3fire.org, Granlund & Granlund, 2011). C3Fire creates an environment whereby teams must work together to resolve a crisis in the firefighting domain, with the goal of evacuating people in critical areas, putting out the forest fire, and protecting buildings and other areas of value from the burning forest fire. This platform makes it possible to study participants' collaborative processes when dealing with a set of crisis scenarios in the context of a simulated emergency response situation. To deal efficiently with the crisis management operation, participants need to prioritize between different objectives, identify and protect critical areas, and plan and implement activities based on given resources. All these tasks are distributed between team members, compelling participants to exchange information and coordinate within and between teams to execute the task. The task is divided into three areas of responsibility as follows: 1) Information and Planning, responsible for situation assessment and providing the operating picture; 2) Operation and Logistic, responsible for intervention and resource management; and 3) Search and Rescue, responsible for research and management of civilians. C3Fire is designed to: 1) achieve an optimal compromise between internal and external validity; 2) show flexibility in scenario configuration (spectrum of units and roles – including search and rescue functions; Tremblay et al., 2010), allowing researchers to capture emergency response and crisis management and rapid response planning; 3) be highly configurable for testing many different types of teams (e.g., hierarchical vs. horizontal organizations); and 4) readily provide objective, non-intrusive metrics for assessing teamwork effectiveness (including macrocognitive functions and team processes) as well as quantitative measures of task performance (that take into account conflicting mission goals). © 2012 ISCRAM.
|
Shuyan Xie, & Markus Helfert. (2011). Towards an information architecture oriented framework for emergency response system. In E. Portela L. S. M.A. Santos (Ed.), 8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011. Lisbon: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Emergency, situations characterized as high consequence, low probability, and short decision time, create a unique decision-making environment that must be conscientiously supported. Historically, one of the techniques business has used to improve complex processes is a maturity model. Organizations should create the capabilities to react to information sharing needs in advance, not react an ad hoc manner to the information crisis. Based on the IT-Capability Maturity Framework (IT-CMF), we detailed some aspects of this model from an information architectural perspective to examine a country wide emergency service. Although information system and information technology (ISIT) have been emphasized in emergency management system, architectural aspects- a structure emphasized semantic description however have been of limited considerations. We propose a framework to analyzing architectural aspects for information sharing that can help improve emergency response system. The framework is discussed and exemplified with a case study. We conclude that the proposed framework provides a deeper understanding of information in use from technical and managerial aspects during emergency response. Guideline for further improvement will be the focus in our future work.
|
Yiewi Li., Yu Guo, & Naoya Ito. (2014). An exploration of a social-cognitive framework for improving the human-centric risk communication. In and P.C. Shih. L. Plotnick M. S. P. S.R. Hiltz (Ed.), ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management (pp. 394–398). University Park, PA: The Pennsylvania State University.
Abstract: With the aim of improving human-centric risk communication, this research in progress paper argues for a social-cognitive perspective focusing on the interaction between laypeople and the information environment. A model is designed to predict laypeople's environmental risk perception and information seeking behavior. Using data from a national online survey (N=1,032), our research is an effort to test the predictive power of the socialcognitive model. Practical implications are also discussed in this paper.
|
Andrea Zielinski, & Ulrich Bügel. (2012). Multilingual analysis of twitter news in support of mass emergency events. In Z.Franco J. R. L. Rothkrantz (Ed.), ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management. Vancouver, BC: Simon Fraser University.
Abstract: Social media are increasingly becoming a source for event-based early warning systems in the sense that they can help to detect natural disasters and support crisis management during or after disasters. In this work-in-progress paper we study the problems of analyzing multilingual twitter feeds for emergency events. The present work focuses on English as “lingua franca” and on under-resourced Mediterranean languages in endangered zones, particularly Turkey, Greece, and Romania Generally, as local civil protection authorities and the population are likely to respond in their native language. We investigated ten earthquake events and defined four language-specific classifiers that can be used to detect earthquakes by filtering out irrelevant messages that do not relate to the event. The final goal is to extend this work to more Mediterranean languages and to classify and extract relevant information from tweets, translating the main keywords into English. Preliminary results indicate that such a filter has the potential to confirm forecast parameters of tsunami affecting coastal areas where no tide gauges exist and could be integrated into seismographic sensor networks. © 2012 ISCRAM.
|