Automating ontology engineering support activities with OnToology

Alobaid, Ahmad; Garijo, Daniel; Poveda‐Villalón, María; Santana-Perez, Idafen; Fernández-Izquierdo, Alba; Corcho, Óscar

doi:10.1016/j.websem.2018.09.003

Cited by 35 publications

(21 citation statements)

References 14 publications

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“…Towards this, they need to assure the active, continuous, decisive participation of all interested parties. To do this, ontologists need to investigate the impact of communitydriven requirements for the ontologies to methodological features and to choose appropriate, widelyknown and used (collaborative) tools, for example, OnToology (Alobaid et al, 2019) and WebProtégé (Tudorache et al, 2009), for facilitating contributions in a selective, familiar and user-friendly way. This should be done throughout the lifetime of the ontology, to be kept alive, evolved and be reused at the maximum level.…”

Section: Oem Trends Findings and Recommendationsmentioning

confidence: 99%

Ontology engineering methodologies for the evolution of living and reused ontologies: status, trends, findings and recommendations

Kotis

Vouros

Spiliotopoulos

2020

The Knowledge Engineering Review

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The aim of this critical review paper is threefold: (a) to provide an insight on the impact of ontology engineering methodologies (OEMs) to the evolution of living and reused ontologies, (b) to update the ontology engineering (OE) community on the status and trends in OEMs and of their use in practice and (c) to propose a set of recommendations for working ontologists to consider during the life cycle of living, evolved and reused ontologies. The work outlined in this critical review paper has been motivated by the need to address critical issues on keeping ontologies alive and evolving while these are shared in wide communities. It is argued that the engineering of ontologies must follow a well-defined methodology, addressing practical aspects that would allow (sometimes wide) communities of experts and ontologists to reach consensus on developments and keep the evolution of ontologies ‘in track’. In doing so, specific collaborative and iterative tool-supported tasks and phases within a complete and evaluated ontology life cycle are necessary. This way the engineered ontologies can be considered ‘shared, commonly agreed and continuously evolved “live” conceptualizations’ of domains of discourse. Today, in the era of Linked Data and Knowledge Graphs, it is more necessary than ever not to neglect to consider the recommendations that OEMs explicitly and implicitly introduce and their implications to the evolution of living ontologies. This paper reports on the status of OEMs, identifies trends and provides recommendations based on the findings of an analysis that concerns the impact of OEMs to the status of well-known, widely used and representative ontologies.

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Section: Oem Trends Findings and Recommendationsmentioning

confidence: 99%

Ontology engineering methodologies for the evolution of living and reused ontologies: status, trends, findings and recommendations

Kotis

Vouros

Spiliotopoulos

2020

The Knowledge Engineering Review

View full text Add to dashboard Cite

show abstract

“…Accordingly, there are some reliable tools that can auto‐generate HTML document from ontology such as Widoco [51], LODE [52], OnToology [53].…”

Section: Methods To Implement Ontologymentioning

confidence: 99%

SARGON – Smart energy domain ontology

et al. 2020

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“…The URIs https: //w3id.org/def/caso# and https://w3id.org/def/irrig# identify the two ontologies. The content negotiation mechanism deployed to publish the ontologies was transparent to ontology developers, as it was managed by OnToology [26]. OnToology is a web-based system that builds on top of Git-based environments and integrates a set of tools for documentation, evaluation and publication activities.…”

Section: Ontology Publication and Maintenancementioning

confidence: 99%

Development Experience of a Context-Aware System for Smart Irrigation Using CASO and IRRIG Ontologies

et al. 2020

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The rapid development of information and communication technologies and wireless sensor networks has transformed agriculture practices. New tools and methods are used to support farmers in their activities. This paper presents a context-aware system that automates irrigation decisions based on sensor measurements. Automatic irrigation overcomes the water shortage problem, and automatic sensor measurements reduce the observational work of farmers. This paper focuses on a method for developing context-aware systems using ontologies. Ontologies are used to solve heterogeneity issues in sensor measurements. Their main goal is to propose a shared data schema that precisely describes measurements to ease their interpretations. These descriptions are reusable by any machine and understandable by humans. The context-aware system also contains a decision support system based on a rules inference engine. We propose two new ontologies: The Context-Aware System Ontology addresses the development of the context-aware system in general. The Irrigation ontology automates a manual irrigation method named IRRINOV®. These ontologies reuse well-known ontologies such as the Semantic Sensor Network (SSN) and Smart Appliance REFerence (SAREF). The decision support system uses a set of rules with ontologies to infer daily irrigation decisions for farmers. This project uses real experimental data to evaluate the implementation of the decision support system.

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Automating ontology engineering support activities with OnToology

Cited by 35 publications

References 14 publications

Ontology engineering methodologies for the evolution of living and reused ontologies: status, trends, findings and recommendations

Ontology engineering methodologies for the evolution of living and reused ontologies: status, trends, findings and recommendations

SARGON – Smart energy domain ontology

Development Experience of a Context-Aware System for Smart Irrigation Using CASO and IRRIG Ontologies

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