SWRL as a Rule Language for Ontology-Based Models in Power Plant Design

Fortineau, Virginie; Paviot, Thomas; Louis-Sidney, Ludovic; Lamouri, Samir

doi:10.1007/978-3-642-35758-9_53

Cited by 19 publications

(6 citation statements)

References 39 publications

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“…Enquiry on existent works [14] about ontologies and formal approaches [6,12,13,16] [7,8] are covering only partially our needs. They are upper level ontologies with insuficient granular precision required to describe resources in our use case.…”

Section: Methodsmentioning

confidence: 99%

Taskradar: Task Visualisation and Monitoring Within Automotive Product Development Lifecycle Using Semantic Technologies

Softic¹,

Rosenberger²,

Turcin³

et al. 2016

Adv. Sci. Technol. Res. J.

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Project management within the automotive production in specific departments is still done separately and does not interact with engineering process. Our work aims on providing flexible data insights on collaboration tasks within such environments. We apply semantic technologies RDF, OWL and SPARQL with a specific domain related ontology PROTARES (PROject TAsks RESources) to interlink, describe and query domain knowledge. As proof of concept we are introducing an experimental visualisation interface called TaskRadar. Our application resides on domain ontology and allows knowledge based browsing and visualisation of tasks in development process. With this example we want to show, how semantically driven customized views can support monitoring and reflection as well as decision-making within the early phases of the automotive product lifecycle.

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Section: Methodsmentioning

confidence: 99%

Taskradar: Task Visualisation and Monitoring Within Automotive Product Development Lifecycle Using Semantic Technologies

Softic¹,

Rosenberger²,

Turcin³

et al. 2016

Adv. Sci. Technol. Res. J.

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“…SWRL rules have been used as the base of reasoning to cover multiples knowledge areas like modelling industrial business processes [37], inferring models of medical insurance fraud detection [38], power plant designs [39], predicting diseases [40], or improving integrated products design [41]. Recently SWRL, has been used in data management research.…”

Section: Related Workmentioning

confidence: 99%

An Ontological-Based Model to Data Governance for Big Data

et al. 2021

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Nowadays, companies and official bodies are using the data as a principal asset to take strategic decision. The advances in big data processing, storage and analysis techniques have allowed to manage the continuous increase in the volume of data. This increase in the volume of data together with its high variability and the large number of sources lead to a constant growing of the complexity of the data management environment. Data governance is the key for simplifying that complexity: it is the element that controls the decision making and responsibilities for all the processes related to data management. This paper discusses an approach to data governance based on ontological reasoning to reduce data management complexity. The proposed data governance system is built over an autonomous system based on distributed components. It uses semantic techniques and automatic ontology-based reasoning, with the different component using a Shared Knowledge Plane to interact. Its fundamental piece is an ontology that represents all the data management processes included in data governance. A prototype of such a system has been implemented and tested for Telefonica´s global video service. The results obtained show the feasibility of using this type of technology to reduce the complexity of managing big data environments.INDEX TERMS Big data, data governance, knowledge-based management, ontologies, reasoning, OWL, SWRL.

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“…Figure 2 presents the diagram of the structure and the architecture of the BNO ontology. As described in Figure 3, we have developed this ontology using the OWL-language [43] using the Protégé editor, version 5.2.0. Protégé 6 is a free, open-source ontology editor and framework for building intelligent systems [44].…”

Section: Codingmentioning

confidence: 99%

“…The aim of this section is to illustrate the proposed BNO ontology for reasoning and inferring new knowledge with sets of rules expressed in SWRL [43].…”

Section: Application Of Bnomentioning

confidence: 99%

BNO—An ontology for understanding the transittability of complex biomolecular networks

Ayadi

Zanni-Merk

Beuvron

et al. 2019

Journal of Web Semantics

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Analysis of biological systems is being progressively facilitated by computational tools. Most of these tools are based on qualitative and numerical methods. However, they are not always evident, and there is an increasing need to provide an additional semantic layer. Semantic technologies, especially ontologies, are one of the tools frequently used for this purpose. Indeed, they are indispensable for understanding the semantic knowledge about the operation of cells at a molecular level. We describe here the biomolecular network ontology (BNO) created specially to address the needs of analysing the complex biomolecular network's behaviour. A biomolecular network consists of nodes, denoting cellular entities, and edges, representing interactions among cellular components. The BNO ontology provides a foundation for qualitative simulation of complex biomolecular networks. We test the performance of the proposed BNO ontology by using a real example of a biomolecular network, the bacteriophage T4 gene 32. We illustrate the proposed BNO ontology for reasoning and inferring new knowledge with sets of rules expressed in SWRL. Results demonstrate that the BNO ontology allows to precisely interpret the corresponding semantic context and intelligently model biomolecular networks and their state changes. The Biomolecular Network Ontology (BNO) is freely available at https://github.com/AliAyadi/BNO-ontology-version-1.0.

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SWRL as a Rule Language for Ontology-Based Models in Power Plant Design

Cited by 19 publications

References 39 publications

Taskradar: Task Visualisation and Monitoring Within Automotive Product Development Lifecycle Using Semantic Technologies

Taskradar: Task Visualisation and Monitoring Within Automotive Product Development Lifecycle Using Semantic Technologies

An Ontological-Based Model to Data Governance for Big Data

BNO—An ontology for understanding the transittability of complex biomolecular networks

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