Offshore wind metadata management

Nguyen, Trinh Hoang; Dunlap, Rocky; Mark, Leo; Prinz, Andreas; Østgren, Bjørn Mo; Friisø, Trond

doi:10.1504/ijmso.2014.065445

Cited by 1 publication

(2 citation statements)

References 40 publications

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“…Offshore wind domain ontology model based on the IEC 61400-25 standard ontology (OWO) by Nguyen et al (2014).…”

Section: Offshore Windmentioning

confidence: 99%

“…These ontologies relied on OWL for knowledge representation. More general, domain-level ontologies and knowledge bases such as WPP ontology (Zhu et al, 2008) and OWO (Nguyen et al, 2014) attempted to comprehensively capture wind-energy-related concepts. These authors of these knowledge bases also opted for a Semantic Web technology stack, with a notable exception of WESgraph, which relied on the Neo4j graph database for data storage and querying.…”

Section: Gcieomentioning

confidence: 99%

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Knowledge engineering for wind energy

Marykovskiy,

Clark,

Day

et al. 2024

Wind Energ. Sci.

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Abstract. With the rapid evolution of the wind energy sector, there is an ever-increasing need to create value from the vast amounts of data made available both from within the domain and from other sectors. This article addresses the challenges faced by wind energy domain experts in converting data into domain knowledge, connecting and integrating them with other sources of knowledge, and making them available for use in next-generation artificial intelligence systems. To this end, this article highlights the role that knowledge engineering can play in the digital transformation of the wind energy sector. It presents the main concepts underpinning knowledge-based systems and summarises previous work in the areas of knowledge engineering and knowledge representation in a manner that is relevant and accessible to wind energy domain experts. A systematic analysis of the current state of the art on knowledge engineering in the wind energy domain is performed with available tools put into perspective by establishing the main domain actors and their needs, as well as identifying key problematic areas. Finally, recommendations for further development and improvement are provided.

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“…Offshore wind domain ontology model based on the IEC 61400-25 standard ontology (OWO) by Nguyen et al (2014).…”

Section: Offshore Windmentioning

confidence: 99%

Section: Gcieomentioning

confidence: 99%