TY - GEN AB - 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. AD - Institute of Structural Engineering (IBK), Swiss Federal Institute of Technology (ETH Zurich), Zurich, Switzerland ; Institute for Energy Technology, Eastern Switzerland University of Applied Sciences (OST), Rapperswil, Switzerland AD - Octue Ltd, British Antarctic Survey, High Cross, Madingley Road, CB3 0ET Cambridge, UK AD - Pacific Northwest National Laboratory, Richland, Washington, USA AD - Fraunhofer Institute for Wind Energy Systems IWES, Bremerhaven, Germany AD - Stacker Group, 708 Altavista Ave., Charlottesville, VA, USA AD - Department of Wind and Energy Systems, Technical University of Denmark, Risø Campus Frederiksborgvej, Roskilde, Denmark AD - Institute of Structural Engineering (IBK), Swiss Federal Institute of Technology (ETH Zurich), Zurich, Switzerland AD - Department of Wind and Energy Systems, Technical University of Denmark, Risø Campus Frederiksborgvej, Roskilde, Denmark AD - School of Management, HES-SO University of Applied Sciences and Arts Western Switzerland Valais AD - Institute of Structural Engineering (IBK), Swiss Federal Institute of Technology (ETH Zurich), Zurich, Switzerland AD - Institute for Energy Technology, Eastern Switzerland University of Applied Sciences (OST), Rapperswil, Switzerland AU - Marykovskiy, Yuriy AU - Clark, Thomas AU - Day, Justin AU - Wiens, Marcus AU - Henderson, Charles AU - Quick, Julian AU - Abdallah, Imad AU - Sempreviva, Anna Maria AU - Calbimonte, Jean-Paul AU - Chatzi, Eleni AU - Barber, Sarah CY - Göttingen, Germany DA - 2024-04 DO - 10.5194/wes-9-883-2024 DO - DOI EP - 883-917 ID - 14349 JF - Wind Energy Science KW - Economie/gestion KW - Informatique L1 - https://arodes.hes-so.ch/record/14349/files/Calbimonte_2024_Knowledge_engineering.pdf L2 - https://arodes.hes-so.ch/record/14349/files/Calbimonte_2024_Knowledge_engineering.pdf L4 - https://arodes.hes-so.ch/record/14349/files/Calbimonte_2024_Knowledge_engineering.pdf LA - eng LK - https://arodes.hes-so.ch/record/14349/files/Calbimonte_2024_Knowledge_engineering.pdf N2 - 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. PB - Copernicus Publications PP - Göttingen, Germany PY - 2024-04 SN - 2366-7451 SP - 883-917 T1 - Knowledge engineering for wind energy TI - Knowledge engineering for wind energy UR - https://arodes.hes-so.ch/record/14349/files/Calbimonte_2024_Knowledge_engineering.pdf VL - 2024, 9 Y1 - 2024-04 ER -