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Arif Cagdas Aydinoglu, Elif Demir, & Serpil Ates. (2011). Designing a harmonized geo-data model for Disaster Management. 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: There are problems for managing and sharing geo-data effectively in Turkey. The key to resolving these problems is to develop a harmonized geo-data model. General features of this model are based on ISO/TC211 standards, INSPIRE Data Specifications, and expectations of Turkey National GIS actions. The generic conceptual model components were defined to harmonize geo-data and to produce data specifications. In order to enable semantic interoperability, application schemas were designed for data themes such as administrative unit, address, cadastre/building, hydrographic, topography, geodesy, transportation, and land cover/use. The model, as base and the domain geo-data model, is a starting point to create sector models in different thematic areas. Disaster Management Geo-data Model model was developed as an extension of base geo-data model to manage geo-data collaborate on disaster management activities. This model includes existing geo-data special for disaster management activities and dynamic data collecting during disaster.
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Carsí, J. A., Canós, J. H., Penadés, Mª C., Sánchez-Díaz, J., & Borges, M. R. S. (2023). Towards a Generic Metamodel for Urban Resilience Assessment. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 1059–1068). Omaha, USA: University of Nebraska at Omaha.
Abstract: The proliferation of natural and artificial disasters in the last decades has made urban resilience enforcement a strategic goal of city governments worldwide and a hot research topic for academics and practitioners. Consequently, several urban resilience assessment and improvement frameworks have been proposed. Some frameworks have associated operational tools, but these systems are not interoperable with other frameworks' utilities, forcing cities to use different tools for evaluating various aspects of resilience. Since data must be converted manually from one tool to another, the conversion may be error-prone and tedious. In this paper, we report the steps toward defining an urban resilience metamodel that intends to be at the core of a multi-framework urban resilience management portal. Our goal is to provide city administrators with a single operational tool able to evaluate resilience according to different frameworks, thanks to the definition of semantic interoperability mechanisms between the frameworks and the metamodel
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Elmhadhbi Linda, Karray Mohamed Hedi, & Archimède Bernard. (2018). Towards an Operational Emergency Response System for Large Scale Situations: POLARISC. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 778–785). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: After a lot of recent natural and human-made disasters all over the word, the large scale emergency response process is becoming very critical and challenging. Lives can be lost and property can be harmed. To respond to these major threats, an effective operational emergency response system needs to address the necessity of data sharing, information exchange and correlation between different Emergency Responders (ERs) including firefighters, police, health care services, army, municipality and so on to successfully respond to large scale disasters. Therefore, the goal of this paper is to introduce POLARISC, an interoperable software solution based on a common and modular ontology shared by all the ERs. Its main objective is to solve the problem of semantic difference and heterogeneity of data to guarantee a common understanding among the various ERs in order to coordinate and to obtain a real time operational picture of the situation.
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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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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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James E. Powell, Linn Marks Collins, & Mark L.B. Martinez. (2009). Using architectures for semantic interoperability to create journal clubs for emergency response. In S. J. J. Landgren (Ed.), ISCRAM 2009 – 6th International Conference on Information Systems for Crisis Response and Management: Boundary Spanning Initiatives and New Perspectives. Gothenburg: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: In certain types of “slow burn” emergencies, careful accumulation and evaluation of information can offer a crucial advantage. The SARS outbreak in the first decade of the 21st century was such an event, and ad hoc journal clubs played a critical role in assisting scientific and technical responders in identifying and developing various strategies for halting what could have become a dangerous pandemic. This research-in-progress paper describes a process for leveraging emerging semantic web and digital library architectures and standards to (1) create a focused collection of bibliographic metadata, (2) extract semantic information, (3) convert it to the Resource Description Framework /Extensible Markup Language (RDF/XML), and (4) integrate it so that scientific and technical responders can share and explore critical information in the collections.
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