Event Details
| Location | Room 4 (Virtual) |
| Date | May 2, 2022 |
| Time | 9:00 AM to 12:00 PM |
A series of tutorials designed to introduce the use of knowledge graphs to an industrial environment (process, manufacturing industries; construction etc.) to technical users with some database experience but not necessarily experience of the use of graphs.
Throughout the tutorials, there is an example ‘thread’ of building models of process plants and equipment with the objective of creating a fit-for-purpose ‘digital twin’ model. This thread culminates with a ‘recipe’ for building fit-for-purpose digital twin models, particularly in the manufacturing and equipment domains.
Session 1: Introduction to graphs
- Graph databases, how they fit in the database landscape, their advantages, and disadvantages.
- What is a knowledge graph database
- Why is it different,
- What are its advantages
- What are its disadvantages
- How to build a graph database
- Triplestores
- Development tools
Session 2: Simple modeling with graphs
- The tools required to build a fit-for-purpose model: RDF, RDFS
- Using RDF, RDFS, and OWL (maybe) to describe graph models
- Creating 1-D models with graphs
- Querying graphs
- with SPARQL
- with OData
Session 3: Creating a realistic plant model: a digital-twin
- Tackling the real requirements of a fit-for-purpose digital-twin model
- What are the issues to be solved applying knowledge graphs to an industrial application
- Limitations of 1D modeling (simple subject-property-object)
- Useful concepts from Basic Formal Ontology
- Extension to 2D modeling (reified statements so we can have other data such as Units-of-measure, accuracy, version and so on)
- Extension to 3D modeling (so we can capture the fact that knowledge is always changing over time)
- Avoiding complex taxonomies with shapes
- TopBraid Composer and/or Protégé for model development
- RDF4J for model deployment and demonstration