Knowledge Graph Data Modeling
Event Details
| Location | Room 2 (Classroom A) |
| Date | May 2, 2022 |
| Time | 3:00 PM to 6:30 PM |
Data scientists, engineers and researchers who have no prior experience in knowledge graph data modelling. In this workshop, we will start from the fundamentals – learning how to think in terms of triples to describe relations of different data objects. If your work involves data analysis, data management, data collaboration or anything data-related, this is a workshop for you to have a brand new insight into how data should be represented and stored.
Tutorial format
- Overview-10 min
- Lecture – 60 mins
- Breaks- 20 minutes
- Hands-on training – 80 mins
- Closing – 10 mins
Tutorial Agenda
Overview-10 min
In this session, we will go through the tutorial structure, introduce TemrinusDB – the open-source tool that we use and pre-flight check to make sure everyone’s set-up is ready.
Lecture – 60 mins
In this session, through slides and presentation, we will go through the fundamental construct of a knowledge graph: – What is triple – What are objects, documents, and other elements in a knowledge graph – Different types of properties Then we will show an example of how data that was represented in a relational database (tables joined with keys) can be reconstructed as a knowledge graph and the elegance of doing so.
Breaks- 20 minutes
A short break, overrun buffer and answering questions.
Hands-on training – 80 mins
At the start of this session, there will be a short tour and demo of how they can build a knowledge graph schema with the schema builder in the TerminusDB Python client. (20 mins)
Then attendees will be given a dataset that is represented in tables and they will need to apply what they learnt in the lecture and construct a schema that works the best for it. They are encouraged to ask questions during this session. (40 mins)
Finally, we will be loading data with the same schema using the Python client. (20mins)
Closing – 10 mins
In this session, we will conclude what the attendee has achieved. We will also provide suggestions if they would like to continue learning how to work with knowledge graphs and acquire related skills.
- A computer with stable internet connection
- TerminusDB Docker image (a.k.a TerminusDB Bootstrap) which you can download for FREE
- Python client for TerminusDB (require Python >=3.7)
- An opened mind and ready to learn something new
By the end of the tutorial, you will be able to think like a knowledge graph expert and construct a proper schema to store your data in a knowledge graph format. You will acquire the skills that you need to build knowledge graphs in TerminusDB – an open-source graph database that enables revisions control and collaborations.
Tutorial Benefits
You will have learnt a new skill set that may assist you in your project in data science or research. You will have a new tool that you can better model your data and collaborate with others. Also, you gain all the prerequisites to use WOQL – a query language for knowledge graphs and the TerminusDB Python client to manage, manipulate and visualize data in your knowledge graph.