The InfraRisk Ontology: Enabling Semantic Interoperability for Critical Infrastructures at Risk from Natural Hazards

Roman, Dumitru; Sukhobok, Dina; Nikolov, Nikolay; Elvesæter, Brian; Pultier, Antoine

doi:10.1007/978-3-319-69459-7_31

Cited by 5 publications

(4 citation statements)

References 6 publications

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“…In the following, we shortly describe each vocabulary. U F D MC #C #R IV HXL Disaster,Geography,Damage, TTL [3], [1], [4], [5] 50 66 [6], [7], [8] Organization, Humanitarian Response [9], [10], [11], [12], [13] MOAC Impact of Crisis, Recovery RDF [3], [14] 70 30 [7], [15] and Response Activities, [10], [16] Geo-locations [17], [18] SMEM Social Media and Emergency --- [19], [20], [21], [22], [7], [8] Management [23], [24], [1], [25], [26], [27] DO Temporal and Spatial Web--97 --Concepts, Impact, App Rehabilitation and Facilities Facilities ERO Report Specification [28], [29], [30], [31], [32] -- [33], [34], [ [37], [19], [20], [8], [7] Crisis Management, Hazard Events…”

Section: State-of-the-art Vocabulariesmentioning

confidence: 99%

Empathi: An Ontology for Emergency Managing and Planning About Hazard Crisis

Shekarpour

Gyrard²,

Sheth³

2019

2019 IEEE 13th International Conference on Semantic Computing (ICSC)

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In the domain of emergency management during hazard crises, having sufficient situational awareness information is critical. It requires capturing and integrating information from sources such as satellite images, local sensors and social media content generated by local people. A bold obstacle to capturing, representing and integrating such heterogeneous and diverse information is lack of a proper ontology which properly conceptualizes this domain, aggregates and unifies datasets. Thus, in this paper, we introduce empathi ontology which conceptualizes the core concepts concerning with the domain of emergency managing and planning of hazard crises. Although empathi has a coarse-grained view, it considers the necessary concepts and relations being essential in this domain. This ontology is available at https://w3id.org/empathi/.

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Section: State-of-the-art Vocabulariesmentioning

confidence: 99%

Empathi: An Ontology for Emergency Managing and Planning About Hazard Crisis

Shekarpour

Gyrard²,

Sheth³

2019

2019 IEEE 13th International Conference on Semantic Computing (ICSC)

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“…Xu and Zlatanova [16] present a hybrid ontology architecture for disaster management and emergency response, and Murgante et al [17] built an ontology in risk prevention and disaster management domain, specifically in the field of seismic risk. Roman et al [18] developed an ontology named InfraRisk to assist publishing and integration of data about transport infrastructure failures in case of natural hazard events.…”

Section: Background and Related Workmentioning

confidence: 99%

Geographic ontology for major disasters: Methodology and implementation

Bouyerbou

Bechkoum

Lepage

2019

International Journal of Disaster Risk Reduction

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During a catastrophic event, the International Charter 1 "Space and Major Disasters" is regularly activated and provides the rescue teams damage maps prepared by a photo-interpreter team basing on pre and post-disaster satellite images. A satellite image manual processing must be accomplished in most cases to build these maps, a complex and demanding process. Given the importance of time in such critical situations, automatic or semiautomatic tools are highly recommended. Despite the quick treatment presented by automatic processing, it usually presents a semantic gap issue. Our aim is to express expert knowledge using a well-defined knowledge representation method: ontologies and make semantics explicit in geographic and remote sensing applications by taking the ontology advantages in knowledge representation, expression, and knowledge discovery. This research focuses on the design and implementation of a comprehensive geographic ontology in the case of major disasters, that we named GEO-MD, and illustrates its application in the case of Haiti 2010 earthquake. Results show how the ontology integration reduces the semantic gap and improves the automatic classification accuracy.

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“…Infrastructure failures caused by natural hazard events were modeled using the InfraRisk ontology. A software prototype using infrared ontology was introduced in [36]. It also provides a visualization of the data published using the ontology.…”

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confidence: 99%

Tsunami-Related Data: A Review of Available Repositories Used in Scientific Literature

Nacházel

Babič

Baiguera

et al. 2021

Water

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Various organizations and institutions store large volumes of tsunami-related data, whose availability and quality should benefit society, as it improves decision making before the tsunami occurrence, during the tsunami impact, and when coping with the aftermath. However, the existing digital ecosystem surrounding tsunami research prevents us from extracting the maximum benefit from our research investments. The main objective of this study is to explore the field of data repositories providing secondary data associated with tsunami research and analyze the current situation. We analyze the mutual interconnections of references in scientific studies published in the Web of Science database, governmental bodies, commercial organizations, and research agencies. A set of criteria was used to evaluate content and searchability. We identified 60 data repositories with records used in tsunami research. The heterogeneity of data formats, deactivated or nonfunctional web pages, the generality of data repositories, or poor dataset arrangement represent the most significant weak points. We outline the potential contribution of ontology engineering as an example of computer science methods that enable improvements in tsunami-related data management.

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The InfraRisk Ontology: Enabling Semantic Interoperability for Critical Infrastructures at Risk from Natural Hazards

Cited by 5 publications

References 6 publications

Empathi: An Ontology for Emergency Managing and Planning About Hazard Crisis

Empathi: An Ontology for Emergency Managing and Planning About Hazard Crisis

Geographic ontology for major disasters: Methodology and implementation

Tsunami-Related Data: A Review of Available Repositories Used in Scientific Literature

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