Training materials
Keywords: FAIR or data sharing
and Target audience: Biomedical researchers or Scientists or data manager or science students or software developers, bioinformaticians
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lessons, e-learning
Introduction to Data Management Practices - Cleaning tabular data with OpenRefine
• beginnerData management Open science FAIR data FAIR CONVERGE -
lessons, e-learning
Introduction to Data Management Practices - Data publication
• beginnerData management Open science FAIR data FAIR CONVERGE -
lessons, e-learning
Introduction to Data Management Practices - Metadata
• beginnerData management FAIR data data organisation FAIR CONVERGE ontologies metadata Controlled vocabularies -
lessons, e-learning
Introduction to Data Management Practices - Data organisation practices
• beginnerData management FAIR data data organisation FAIR CONVERGE -
lessons, e-learning
Introduction to Data Management Practices - Open Science and FAIR
• beginnerData management Open science FAIR data FAIR CONVERGE -
Video, E-Learning
How to create a concept for the SPHN Dataset
• beginnerComputer science Data management FAIR data Medical informatics Design Standardisation and normalisation Clinical data Semantic Framework FAIR Concepts design Ontology Semantic inheritance SNOMED CT Conceptualization -
Slides
FAIR data - Module 4 (share and publish data)
• beginnerBioinformatics Biology Data management data sharing Data publishing legal framework data warehouse licensing data reuse -
Slides
FAIR data - Module 3 (Metadata)
• beginnerBioinformatics Biology Data management Data handling metadata data annotation life science standards data sharing -
Training materials
FAIR principles applied to bioinformatics
•• intermediateFAIR Reproducible Science Open science Data analysis Data processing -
Training materials
Essential Steps of the FAIRification Process
•• intermediateFAIR data stewardship metadata linked data
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