Wind Energy Science
Wind Energy Science
WES
Articles | Volume 9, issue 4
Articles | Volume 9, issue 4
https://doi.org/10.5194/wes-9-883-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-9-883-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 9, issue 4
Review article
 | 
12 Apr 2024
Review article |  | 12 Apr 2024

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, and Sarah Barber

Viewed

Total article views: 7,737 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
6,475 1,142 120 7,737 122 187
  • HTML: 6,475
  • PDF: 1,142
  • XML: 120
  • Total: 7,737
  • BibTeX: 122
  • EndNote: 187
Views and downloads (calculated since 03 Jan 2024)
Cumulative views and downloads (calculated since 03 Jan 2024)

Viewed (geographical distribution)

Total article views: 7,737 (including HTML, PDF, and XML) Thereof 7,298 with geography defined and 439 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 26 Mar 2026
Download
Short summary
This paper delves into the crucial task of transforming raw data into actionable knowledge which can be used by advanced artificial intelligence systems – a challenge that spans various domains, industries, and scientific fields amid their digital transformation journey. This article underscores the significance of cross-industry collaboration and learning, drawing insights from sectors leading in digitalisation, and provides strategic guidance for further development in this area.
Read more
Share
Altmetrics
Final-revised paper
Preprint