Video, Training materials, E-learning
Expanding the SPHN RDF Schema
Note: Since the release of the 2023.1 version of the SPHN Semantic Interoperability Framework, SPHN has implemented an automated approach for generating semantic artifacts. This process utilizes the SPHN Schema Forge and the SPHN Dataset Template. For more detailed information, we encourage you to refer to the following training material:
Expanding the SPHN RDF Schema is a training that was developed in the context of the Swiss Personalized Health Network (SPHN) initiative and is part of a series of trainings centered around the SPHN Interoperability Framework developed by the SPHN Data Coordination Center (DCC). The framework aims at facilitating collaborative research by providing a decentralized infrastructure sustained by a strong semantic layer (SPHN Dataset) and graph technology, based on RDF, for the exchange and storage of data.
As projects comes with specific needs, the SPHN Dataset and its related RDF schema can be extended to cover their requirements. This training highlights the necessary steps that lead to an extension of the SPHN RDF schema using an example concept -Fluid Balance- and Protégé, a desktop-tool for editing ontologies.
Prerequisites:
- Basic understanding of ontologies and RDF
- Basic understanding of the SPHN Interoperability Framework strategy
After the training you will be able to:
- Understanding SPHN’s strategy for projects
- Load the SPHN template ontology into Protégé
- Build an ontology (classes, properties) in Protégé by expanding the SPHN RDF schema with an example concept.
Resources:
All resources are available on the training's GitLab space
Licence: Creative Commons Attribution Share Alike 4.0 International
Keywords: Clinical data, Data semantics, FAIR, Ontology editing, Protegé, RDF, OWL
Target audience: Research Scientists, Data Managers, Biomedical Researchers, Bioinformaticians, Data Scientists
Resource type: Video, Training materials, E-learning
Status: Archived
Contributors: Kristin Gnodke, Sabine Österle
Scientific topics: Ontology and terminology, Medical informatics, FAIR data, Data management, Computer science
Operations: Data editing, Ontology visualisation, Visualisation, Data handling
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