Training materials
Difficulty level: Intermediate
and Target audience: Bachelor students or Data Scientists or EIP members or computational scientists or policy officer or programmers
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Presentation
FAIRtracks and Omnipy – FAIRtracks interoperability story
•• intermediateData submission, annotation, and curation Data identity and mapping Data quality management Data governance Workflows Data handling -
Video, E-Learning
SPHN Dataset Template: Build an RDF schema from an Excel file
•• intermediateComputer science Data management FAIR data Medical informatics Semantic artifacts generation Automation Clinical data Semantic Framework FAIR RDF RDF graph generation Dataset template -
Video, Training materials, E-learning
Validate Graph Data with SHACL
•• intermediateMedical informatics FAIR data Data management Computer science Validation Data handling Clinical data SHACL Data validation RDF Knowledge graph GraphDB RDF graph validation -
Video, Training materials, Mock data, E-learning
How to use Python and R with RDF Data
•• intermediateComputer science Data management FAIR data Medical informatics Query and retrieval Data handling Data retrieval Clinical data SPARQL Query data RDF Knowledge graph Python R GraphDB -
Training materials
FAIR principles applied to bioinformatics
•• intermediateFAIR Reproducible Science Open science Data analysis Data processing