Learn to design and create ontologies with an ontology editor.
Provenance is very important not only to describe how data is collected, but also for regenerating and reproducing results. Provenance records how data is created, providing very useful context for understanding data.
When data is represented with standard formats, it is easier to use and integrate with other data. How are standards designed?
Reporting the results of any data analysis must be done in a systematic way according to best practices for publishing, preserving, and disseminating data and software.
Privacy and ethics in data science Any data analysis should handle appropriately any sensitive data, and respect people’s right to privacy. Learn recent techniques for protecting sensitive data, and understand their limitations and any potential for breaches of privacy in your work.