Ontology Design Patterns for Representing Knowledge in the Disaster Risk Domain

Mazimwe, Allan; Hammouda, Imed; Gidudu, Anthony

doi:10.1109/wetice.2019.00066

Cited by 3 publications

(2 citation statements)

References 9 publications

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“…Conflict of interest This work is an extended paper [47] of the 28th IEEE WETICE conference that took place in Anacapri, Naples, Italy, June 12-14, 2019. The authors declare that they have no other conflict of interest.…”

Section: Compliance With Ethical Standardsmentioning

confidence: 99%

A Pattern Driven Approach to Knowledge Representation in the Disaster Domain

et al. 2020

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Access to integrated disaster-related data through querying is still a problem due to associated semantic barriers. The disaster domain largely relies on the top-down approach of ontology development. This limits reuse due to associated commitments and complex alignments within ontologies. Therefore, there is a need to utilize a bottom-up approach that reuses patterns for representing disaster knowledge. To bridge the availability gap of patterns for representing disaster knowledge, this study identifies existing and emerging patterns for reuse while organizing disaster data from multiple sector stakeholders. Based on the eXtreme Design (XD) methodology and key informant interviews, competency questions (CQs) were elicited from domain stakeholders. The CQs are matched with existing patterns from other contexts. Emerging patterns (e.g the Event Classification and Quality Dependence Description for Objects) are also developed for CQs not captured and subsequently tested using SPARQL queries characterising the CQs. It is in this context that this paper presents a characterisation of disaster risk knowledge using CQs and corresponding patterns (reusable and emerging) covering the knowledge. Accordingly, we illustrate a pattern-driven use case to organise drought hazard data for early warning purposes. This provides a powerful use case for adopting a pattern-based approach to knowledge representation in the disaster domain.

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Section: Compliance With Ethical Standardsmentioning

confidence: 99%

A Pattern Driven Approach to Knowledge Representation in the Disaster Domain

et al. 2020

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“…P75 Ontology for Vulnerability Assessments[91] Ontology for Vulnerability Assessments implemented in the VUWIKI P62 Ontology model for hazard identification[92] Models knowledge used in rapid risk estimation for hazard scenarios P86 QualityCausation[93] Represents causation of qualities of an object that participates in a hazard eventP72 Referential quality ODP [94], Represents knowledge for qualities(such as notions affordance, resilience and vulnerability) of an entity with reference to an external factor RECOVERY PHASE P30 Disaster domain ontology [95] Concepts based on Critical GEOS Earth Observation Parameters and Social Benefit Area P48 Dynamic Flood Ontology (DFO) [96] Models spatial-temporal changes of flood situation for disaster monitoring purposes PREVENTION, MITIGATION AND PREPAREDNESS PHASES P70 Disaster resilient construction operations (DRCOs-Onto) [97] Defines knowledge for whole life-cycle disaster management of construction projects P67 Landslip Ontology [98] Unified knowledge representation for EO data discovery of during landslide hazard verification and analysis in EWS. P59 SWRO-DDPM ontology [99] Defines concepts for sensors, observation and model resources for dynamic disaster processing P45 Urban Industrial Disaster Warning ontology [100]Represents knowledge for technology event in the context of urban industrial disaster warning.OTHERSP1 Ontology for DRR learning resources[101,102] Enhance the sharing of knowledge and learning about disaster risk reduction.…”

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confidence: 99%

Implementation of FAIR Principles for Ontologies in the Disaster Domain: A Systematic Literature Review

Mazimwe

Hammouda

Gidudu

2021

IJGI

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The success of disaster management efforts demands meaningful integration of data that is geographically dispersed and owned by stakeholders in various sectors. However, the difficulty in finding, accessing and reusing interoperable vocabularies to organise disaster management data creates a challenge for collaboration among stakeholders in the disaster management cycle on data integration tasks. Thus the need to implement FAIR principles that describe the desired features ontologies should possess to maximize sharing and reuse by humans and machines. In this review, we explore the extent to which sharing and reuse of disaster management knowledge in the domain is inline with FAIR recommendations. We achieve this through a systematic search and review of publications in the disaster management domain based on a predefined inclusion and exclusion criteria. We then extract social-technical features in selected studies and evaluate retrieved ontologies against the FAIR maturity model for semantic artefacts. Results reveal that low numbers of ontologies representing disaster management knowledge are resolvable via URIs. Moreover, 90.9% of URIs to the downloadable disaster management ontology artefacts do not conform to the principle of uniqueness and persistence. Also, only 1.4% of all retrieved ontologies are published in semantic repositories and 84.1% are not published at all because there are no repositories dedicated to archiving disaster domain knowledge. Therefore, there exists a very low level of Findability (1.8%) or Accessibility (5.8%), while Interoperability and Reusability are moderate (49.1% and 30.2 % respectively). The low adherence of disaster vocabularies to FAIR Principles poses a challenge to disaster data integration tasks because of the limited ability to reuse previous knowledge during disaster management phases. By using FAIR indicators to evaluate the maturity in sharing, discovery and integration of disaster management ontologies, we reveal potential research opportunities for managing reusable and evolving knowledge in the disaster community.

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Design of a Modular Ontology for South African Informal Sector Services

Atoba

Daramola

2022

Proceedings of Seventh International Congress on Information and Communication Technology

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Ontology Design Patterns for Representing Knowledge in the Disaster Risk Domain

Cited by 3 publications

References 9 publications

A Pattern Driven Approach to Knowledge Representation in the Disaster Domain

A Pattern Driven Approach to Knowledge Representation in the Disaster Domain

Implementation of FAIR Principles for Ontologies in the Disaster Domain: A Systematic Literature Review

Design of a Modular Ontology for South African Informal Sector Services

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