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Validating semantic knowledge graphs using SHACL

A talk by Veronika Heimsbakk
Senior Consultant, AI & Data Science, Capgemini

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About this talk

Prior to the Shape Constraint Language (SHACL) we had no W3C standardization for validation our semantic knowledge graphs against a set of constraints.

By constraining RDF using SHACL we gain the possibility of exactly this—validating semantic knowledge graphs under a closed world assumption!

This masterclass will introduce you to the SHACL Core constraints, demonstrate how to constrain your data and what happens if the data conforms false (or true for that matter!).

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Goals:

  • Learn about the SHACL Core constraints
  • Gain hands-on experience for constraining your RDF data using SHACL and identifying errors in validation reports

Key Topics:

  • Terminology and concepts of semantic knowledge graphs
  • Comparing SHACL and the Web Ontology Language (OWL)
  • Introduction to SHACL
  • Hands-on:
    • Building shapes for ABoxes
    • Validation and validation errors

Target Audience:

  • Information architects
  • Content creators
  • Data modellers
  • People interested in high data integrity

Level:

  • Beginner/Intermediate (depending on your prior knowledge of SHACL)

Prerequisites:

  • Some knowledge and/or experience with RDF is needed.

Format:

  • The first part includes a traditional lecture
  • Followed by a hands-on session that participants can follow in their editor of choice

Outline:

  • Lecture including
    • Basis terminology, concepts and history
    • Introduction to SHACL Core constraints
  • Hands-on demonstration
    • A brief look at some data examples
    • Building constraints from scratch, using SHACL Core
    • Using validation engine (SHACL playground and through a Java framework)
  • Summary
    • Discussion, Q&A, resources

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Veronika Heimsbakk

Senior Consultant | Data Science & AI | Insights & Data | Capgemini

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