Knowledge Engineering for Wind Energy
Yuriy Marykovskiy, Thomas Clark, Justin Day, Marcus Wiens, Charles, Henderson, Julian Quick, Imad Abdallah, Anna Maria Sempreviva, Jean-Paul, Calbimonte, Eleni Chatzi, Sarah Barber

TL;DR
This paper explores how knowledge engineering can facilitate the digital transformation of the wind energy sector by converting data into actionable knowledge for intelligent systems.
Contribution
It provides a systematic analysis of current knowledge engineering practices in wind energy and offers guidelines for future development and integration.
Findings
Identified key challenges in knowledge conversion and integration.
Reviewed existing tools and methods in wind energy knowledge engineering.
Proposed guidelines for advancing knowledge-based systems in wind energy.
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, as well as from other sectors. This article addresses the challenges faced by wind energy domain experts in converting data into domain knowledge, connecting and integrating it with other sources of knowledge, and making it available for use in next generation artificially intelligent systems. To this end, this article highlights the role that knowledge engineering can play in the process of 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 domain experts. A systematic analysis of the current state-of-the-art…
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