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An ontology hosting portal for enhancing data sharing in wind energy

Capture d'écran 2024-05-29 001807

Funding Agency: swissuniversities CHORD

Duration: 2024-2025

Partners: OST Eastern Switzerland University of Applied Sciences  

A lack of data sharing is one of the largest hurdles to innovation in the wind energy sector. To successfully share data and implement open science principles, domain-specific ontologies and other semantic artefacts need to be adopted by the community. Most existing conceptual models in wind energy and related domains are not published following the linked data principles or FAIR guidelines. Therefore, the aims of this project are to (1) prototype a public ontology hosting portal for the technology sciences domain, and (2) use it to build up a community of users in the wind energy sector. First, the packaged OntoPortal Virtual Appliance will be forked and used to host a new public “TechnoPortal”. A community of users will then be built up using WeDoWind, a framework developed for creating mutually beneficial collaborations using the idea of “challenges”. The WeDoWind Wind Energy Ecosystem consists of 300+ people actively collaborating and sharing data around multiple “challenges”. For this part, existing semantic artefacts related to wind energy will first be evaluated, chosen and hosted on the TechnoPortal. Then, WeDoWind “challenges” will be run in order to bring the community together to develop new ontologies and conceptual data models for specific tasks, such as describing coordinate systems on a wind turbine. Finally, the new ontologies will be applied and tested on real data shared via WeDoWind “challenges”. The activities will be communicated as part of the IEA Wind Task 43 Metadata Challenge webinar series and connected training activities for sustainability 


Demos


News

  • 01.2024: Kick-off of the project.

Publications

  •  Knowledge engineering for wind energy. Y. Marykovskiy, T. Clark, J. Day, M. Wiens, C. Henderson, J. Quick, I. Abdallah, A. M. Sempreviva, J.-P. Calbimonte, E. Chatzi & S. Barber. Wind Energy Science 9, 4 883-917. 2024. https://doi.org/10.5194/wes-9-883-2024  
  • Knowledge Engineering for Wind Energy. Y. Marykovskiy, T. Clark, J. Day, M. Wiens, C. Henderson, J. Quick, I. Abdallah, A. M. Sempreviva, J.-P. Calbimonte, E. N. Chatzi & S. Barber. CoRR Cmputing Research Repository abs/2310.00804, 2023. https://doi.org/10.48550/ARXIV.2310.00804