Exploring ontologies for semantic interoperability of data in emergency response

Fan, Zhao; Zlatanova, Sisi

doi:10.1007/s12518-011-0048-y

Cited by 38 publications

(20 citation statements)

References 28 publications

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“…Cohn (1997) proposed that the humancomputer interaction in GIS should be more concise and accurate than it is currently. Currently, aiming at resolving semantic diversity generating adverse effect on data management and achieving semantic interoperation among heterogeneous data, spatial semantic description has been used in disaster data management (Fan and Zlatanova, 2011;Li et al, 2007;Zhu et al, 2009;Schulz et al, 2012;Silva et al, 2013). Schulz (2012) and Silva (2013) established description of data by Linked Open Data (LOD).…”

Section: Related Work On the Semantic Technology In Disaster Data Manmentioning

confidence: 99%

“…3) Recent disaster data retrieval mainly relies on querying with keywords of metadata passively. The artificial experience plays an important role in finding available data because there is short of mechanism of automatically discovering related data and disaster knowledge for computer reasoning (Fan and Zlatanova, 2011). In practice, trivial and time-consuming operations to integrate various resources have cost most the manual resources rather than improving the decision-making (Laniak et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

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A Task-Driven Disaster Data Link Approach

Qiu

Zhu

et al. 2015

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:With the rapid development of sensor networks and Earth observation technology, a large quantity of disaster-related data is available, such as remotely sensed data, historic data, cases data, simulation data, disaster products and so on. However, the efficiency of current data management and service systems has become increasingly serious due to the task variety and heterogeneous data. For emergency task-oriented applications, data searching mainly relies on artificial experience based on simple metadata index, whose high time-consuming and low accuracy cannot satisfy the requirements of disaster products on velocity and veracity. In this paper, a task-oriented linking method is proposed for efficient disaster data management and intelligent service, with the objectives of 1) putting forward ontologies of disaster task and data to unify the different semantics of multi-source information, 2) identifying the semantic mapping from emergency tasks to multiple sources on the basis of uniform description in 1), 3) linking task-related data automatically and calculating the degree of correlation between each data and a target task. The method breaks through traditional static management of disaster data and establishes a base for intelligent retrieval and active push of disaster information. The case study presented in this paper illustrates the use of the method with a flood emergency relief task.

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Section: Related Work On the Semantic Technology In Disaster Data Manmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Task-Driven Disaster Data Link Approach

Qiu

Zhu

et al. 2015

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…Fan and Zlatanova have used ontologies for semantic interoperability in disaster management [16]. The proposed methodology comprises two phases.…”

Section: Related Workmentioning

confidence: 99%

A Disaster Document Classification Technique Using Domain Specific Ontologies

Ilyas¹

2015

ijacsa

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Abstract-Manual data collection and entry is one of the bottlenecks in conventional disaster management information systems. Time is a critical factor in emergency situations and timely data collection and processing may help in saving several lives. An effective disaster management system needs to collect data from World Wide Web automatically. A prerequisite for data collection process is document classification mechanism to classify a particular document into different categories. Ontologies are formal bodies of knowledge used to capture machine understandable semantics of a domain of interest and have been used successfully to support document classification in various domains. This paper presents an ontology-based document classification technique for automatic data collection in a disaster management system. A general ontology of disasters is used that contains the description of several natural and manmade disasters. The proposed technique augments the conventional classification measures with the ontological knowledge to improve the precision of classification. A preliminary implementation of the proposed technique shows promising results with up to 10% overall improvement in precision when compared with conventional classification methods.

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“…The ontology described in [15] presents a model for the organization of dynamic data for emergency response developed within the RGI-239 project 'Geographical Data Infrastructure for Disaster Management' (GDI4DM). It applies ontologies to resolve the semantic interoperability inherent in emergency management.…”

Section: Related Workmentioning

confidence: 99%

Semantic reasoning for intelligent emergency response applications

Hristoskova

Ongenae

Turck

2013

2013 11th IEEE International Conference on Industrial Informatics (INDIN)

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Abstract-Emergency response applications require the processing of large amounts of data, generated by a diverse set of sensors and devices, in order to provide for an accurate and concise view of the situation at hand. The adoption of semantic technologies allows for the definition of a formal domain model and intelligent data processing and reasoning on this model based on generated device and sensor measurements. This paper presents a novel approach to emergency response applications, such as fire fighting, integrating a formal semantic domain model into an event-based decision support system, which supports reasoning on this model. The developed model consists of several generic ontologies describing concepts and properties which can be applied to diverse context-aware applications. These are extended with emergency response specific ontologies. Additionally, inference on the model performed by a reasoning engine is dynamically synchronized with the rest of the architectural components. This allows to automatically trigger events based on predefined conditions. The proposed ontology and developed reasoning methodology is validated on two scenarios, i.e. (i) the construction of an emergency response incident and corresponding scenario and (ii) monitoring of the state of a fire fighter during an emergency response.

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Exploring ontologies for semantic interoperability of data in emergency response

Cited by 38 publications

References 28 publications

A Task-Driven Disaster Data Link Approach

A Task-Driven Disaster Data Link Approach

A Disaster Document Classification Technique Using Domain Specific Ontologies

Semantic reasoning for intelligent emergency response applications

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