An introduction to Semantic Python

A CrashCourse introduction to semantic data using Python covering a number of frameworks such as rdflib, owlready and pySHACL

Semantic Python

Course Content

This CrashCourse is an introduction to semantic data using Python. It covers the following topics:

  • We learn to work with RDF graphs using rdflib
  • We explore the owlready package and OWL ontologies
  • We look into json-ld serialization of RDF/OWL data
  • We try data validation using pySHACL
  • We use throughout a realistic data set based on the Credit Ratings Ontology

Who Is This Course For

The course is useful to:

  • Developers
  • Data Scientists
  • Quantitative Risk Managers

How Does The Course Help

Mastering the course content provides background knowledge towards the following activities:

  • Acquiring and processing data expressed using semantic technologies (RDF / OWL / JSON-LD)
  • Converting date from formats such as JSON to semantic formats
  • Validating semantic data

What Will You Get From The Course

  • You will be able to have an overview of what python tools are currently available to work with semantic data
  • You will be able to plan further study to deepen your knowledge of this technology stack

Course Level and Difficulty Level

This course is part of the Data Science family.

  • This is a Core Level course in Data Science, which means that good grounding at Introductory level in Python and other Data Science tools / concepts is a prerequisite for making the most out of this course.
  • The domain of the course is primarily Semantic Data using Python which means some familiarity with data, markup languages and file formats is required.
  • This is a Technical course which means technology elements (such as installing and running Python programs) are essential for mastering the material.

If you have not taken an Open Risk Academy course before, the CrashCourse Academy Demo provides a quick overview of the Academy.

Course Material

The course material comprises the following:

  • Five interactive readings
  • Embedded exercises
  • Scripts and Data sets available at our github repo

Time Requirements and Important Dates

  • The course is self-paced and can be undertaken at any point.
  • Depending on your background knowledge it requires a commitment of about two-three hours total for a quick overview.
  • The domain covered is quite extensive, if you insert detours to learn about RDF/OWL/Semantic Data through the further reading suggestions it could take significantly more time to complete.

Where To Get Help

If you get stuck on any issue with the course or the Academy:

  • If the issue is related to the course topics / material, check in the first instance the Course Forum (Chat) or our gitter channel
  • If the issue is related the operation of the Open Risk Academy check first the Academy FAQ.
  • If the issue persists contact us at info at openrisk dot eu