Until now, it has been fairly difficult for learners to readily access curated materials on the topic of knowledge graph, largely due to the fairly patchy and technical landscape that we need to navigate when trying to understand the subject area. This course is a game changer, bringing to life the starting point for your journey to becoming an expert in knowledge graph technology, semantics and ontologies.
Read more
Until now, it has been fairly difficult for learners to readily access curated materials on the topic of knowledge graph, largely due to the fairly patchy and technical landscape that we need to navigate when trying to understand the subject area. This course is a game changer, bringing to life the starting point for your journey to becoming an expert in knowledge graph technology, semantics and ontologies.
Until now, it has been fairly difficult for learners to readily access curated materials on the topic of knowledge graph, largely due to the fairly patchy and technical landscape that we need to navigate when trying to understand the subject area. This course is a game changer, bringing to life the starting point for your journey to becoming an expert in knowledge graph technology, semantics and ontologies.
A knowledge graph can be defined as a network of facts connected via explicitly defined relationships, from which new knowledge can be inferred, and a knowledge graph may have an underlying schema (a.k.a ontology) for organising the entities within the network.
There is a technology stack that underpins knowledge graphs, which unlocks countless use cases focused on tearing down data silos, richly representing data & metadata, augmenting data architecture with semantics (i.e meaning in computation form), and driving next-level AI and analytics.
Organisations across various sectors like Manufacturing, Telecommunication, IT, Mass Media, Financial Services and Pharmaceutical are applying knowledge graph technology to realise their data strategies and digital transformation. Knowledge graphs are a powerful enabler for modern data architectures integral to Industry 4.0, Digital Twins, intelligent decision support ecosystems, explainable AI, and many more.
This course is aimed at leaners, such as data-focused professionals, with an interest in the latest trends in information modelling, data architecture, knowledge representation and classification, and with no prior exposure to knowledge graph technologies. It's your guaranteed stepping stone to a solid foundation, ensured to make you become comfortable with jargon used in the field of knowledge graph, ontologies and semantics. You will also be able to articulate the importance of knowledge graphs, their underlying architecture and industry applications, as well as identify opportunities for applying 'graph thinking'.
What's inside
Learning objectives
- Become familiar with jargon used in the field of knowledge graph, ontologies and semantics
- Articulate the importance of knowledge graphs, their underlying architecture and industry applications
- Forge a solid foundation for progressing to intermediate and advanced areas of knowledge engineering
- Identify opportunities for applying 'graph thinking'
- Become familiar with jargon used in the field of knowledge graph, ontologies and semantics
- Articulate the importance of knowledge graphs, their underlying architecture and industry applications
- Forge a solid foundation for progressing to intermediate and advanced areas of knowledge engineering
- Identify opportunities for applying 'graph thinking'
Syllabus
Gain an understanding of the context of the course, its scope, audience and learning outcomes.
This is the very first lecture of this course, where we'll go through introductions and set the scene for the course.
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Syllabus
This is the very first lecture of this course, where we'll go through introductions and set the scene for the course.
This is a simple activity where you will use a visual graph to navigate through different content topics.
In this lecture, we'll go through some important ideas that are central to knowledge graphs and that we can draw out from the previous activity.
This lesson provides a concise definition for what a Knowledge Graph is.
This lesson clarifies the course structure, its intended audience and highlights all the key learning outcomes you will benefit from.
Here, you will find a decision tree diagram that will help you decide whether this course is really what you are after.
This lecture explores the idea of a network of data, which is a fundamental building block of a knowledge graph.
This lecture explores the idea of weaving data using explicitly identifiable relationships in order to bring meaning to connections.
With the interwoven 'mesh' of information, it's possible to add business rules to a knowledge graph to support knowledge discovery. This is the idea of inferable knowledge - a key strength of knowledge graph.
Knowledge graph schemas are flexible and easy to incorporate and amend. In this lecture, we introduce the concept of 'ontology', a specialist term to mean a knowledge graph schema.
This quiz will test your understanding of what a knowledge graph is.
In this activity, you will watch a short TED Talk about "A Visual History of Human Knowledge" by Manuel Lima.
This quiz will test your understanding of how knowledge has been represented and evolved over time.
This lecture explores the importance of connections and why they matter for transforming data into knowledge.
Knowledge graph owes its origin to Graph Theory. In this lecture, we briefly touch on this aspect.
Here, we will explore the different core components of the knowledge graph architecture.
In this lecture, you will be able to recognise the key differences between knowledge graph-based systems and relational database management systems.
In this lesson, we will look at the graph technology landscape. This landscape is getting busier and busier with several vendors and companies delivering various capabilities and use cases.
Agile development methodology can be applied to knowledge graph development. This lecture focuses on the Scrum methodology for developing knowledge graphs, backed by useful examples.
This is a continuation of the previous lecture looking at different approaches for when to deploy ontologies as part of the build methodology.
This quiz will test your understanding of what knowledge graph technology.
This lecture discusses the Linked Data use case.
This lecture discusses the Semantic Search use case.
This lecture discusses the Semantic Federation use case as part of the bigger theme of semantic interoperability.
This lecture discusses the Enterprise Knowledge Graph use case.
Generative AI and LLMs can hallucinate. To prevent this from happening, we can make use of knowledge graphs as part of a RAG architecture.
This lecture discusses various other use cases for knowledge graph.
This quiz will test your understanding of the applications and use cases that knowledge graphs can unlock.
This lecture touches on the place knowledge graph technology occupies in data architecture, its relevance to AI and Machine Learning, the concept of explainability, and how users are intended to consume information coming from knowledge graph through familiar views.
This is the concluding lecture for this series. Hope you've enjoyed the course!
Download course slides.
Attributions, special thanks and disclaimer.
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Reviews summary
Essential intro to knowledge graphs
Highlights real-world applications for data professionals.
Provides a strong base for further exploration in the field.
Simplifies complex knowledge graph concepts for newcomers.
Activities
SQL
Show steps
Review the basics of SQL to ensure proficiency before starting the course.
Browse courses on
SQL
Show steps
-
Review the SQL syntax for creating tables, inserting data, and querying data.
-
Practice writing SQL queries to retrieve data from a database.
-
Complete online tutorials or exercises on SQL.
Review Ontology Engineering Guidelines
Show steps
Examine the principles of ontology engineering to understand best practices for knowledge graph development.
Browse courses on
Ontology
Show steps
-
Review ontological engineering guidelines and resources.
Knowledge Graph Tutorial
Show steps
Complete a guided tutorial on knowledge graphs to gain a deeper understanding of the concepts and technologies.
Show steps
-
Find a reputable online tutorial or course on knowledge graphs.
-
Follow the tutorial step-by-step, taking notes and completing any exercises.
-
Apply the concepts learned in the tutorial to a small personal project.
Six other activities
Expand to see all activities and additional details
Show all nine activities
Attend a Knowledge Graph Meetup
Show steps
Connect with others interested in knowledge graphs at a local meetup or online event.
Show steps
-
Find a knowledge graph meetup or event in your area.
-
Attend the event and introduce yourself to others.
-
Participate in discussions and ask questions.
Knowledge Graph Resources Database
Show steps
Compile a comprehensive list of resources related to knowledge graphs, including tutorials, tools, and datasets.
Show steps
-
Search for and gather resources on knowledge graphs from various sources.
-
Organize and categorize the resources into a structured database.
-
Share the database with other students or interested individuals.
Knowledge Graph Query Practice
Show steps
Practice querying knowledge graphs using SPARQL or other query languages.
Show steps
-
Find a dataset or knowledge graph that is publicly available.
-
Write SPARQL queries to retrieve specific information from the knowledge graph.
-
Test and refine your queries to optimize performance and accuracy.
Contribute to a Knowledge Graph Project
Show steps
Contribute to the development of an open-source knowledge graph project.
Show steps
-
Find an open-source knowledge graph project that aligns with your interests.
-
Identify an area where you can contribute, such as data collection, model development, or documentation.
-
Contact the project maintainers and express your interest in contributing.
-
Follow the project's contribution guidelines and submit your changes.
Knowledge Graph Modeling Project
Show steps
Develop a small-scale knowledge graph model for a specific domain or topic.
Show steps
-
Choose a domain or topic of interest.
-
Identify the key entities, relationships, and properties in your domain.
-
Design and implement a knowledge graph model using an appropriate technology.
-
Populate your knowledge graph with data.
-
Query and explore your knowledge graph to demonstrate its functionality.
Mentor a Knowledge Graph Beginner
Show steps
Share your knowledge by mentoring someone new to the field of knowledge graphs.
Show steps
-
Identify a beginner who is interested in learning about knowledge graphs.
-
Set up regular meetings or communication channels for mentoring.
-
Provide guidance, support, and resources to help the beginner develop their knowledge and skills.
SQL
Show steps
Review the basics of SQL to ensure proficiency before starting the course.
Browse courses on
SQL
Show steps
- Review the SQL syntax for creating tables, inserting data, and querying data.
- Practice writing SQL queries to retrieve data from a database.
- Complete online tutorials or exercises on SQL.
Review Ontology Engineering Guidelines
Show steps
Examine the principles of ontology engineering to understand best practices for knowledge graph development.
Browse courses on
Ontology
Show steps
- Review ontological engineering guidelines and resources.
Knowledge Graph Tutorial
Show steps
Complete a guided tutorial on knowledge graphs to gain a deeper understanding of the concepts and technologies.
Show steps
- Find a reputable online tutorial or course on knowledge graphs.
- Follow the tutorial step-by-step, taking notes and completing any exercises.
- Apply the concepts learned in the tutorial to a small personal project.
Attend a Knowledge Graph Meetup
Show steps
Connect with others interested in knowledge graphs at a local meetup or online event.
Show steps
- Find a knowledge graph meetup or event in your area.
- Attend the event and introduce yourself to others.
- Participate in discussions and ask questions.
Knowledge Graph Resources Database
Show steps
Compile a comprehensive list of resources related to knowledge graphs, including tutorials, tools, and datasets.
Show steps
- Search for and gather resources on knowledge graphs from various sources.
- Organize and categorize the resources into a structured database.
- Share the database with other students or interested individuals.
Knowledge Graph Query Practice
Show steps
Practice querying knowledge graphs using SPARQL or other query languages.
Show steps
- Find a dataset or knowledge graph that is publicly available.
- Write SPARQL queries to retrieve specific information from the knowledge graph.
- Test and refine your queries to optimize performance and accuracy.
Contribute to a Knowledge Graph Project
Show steps
Contribute to the development of an open-source knowledge graph project.
Show steps
- Find an open-source knowledge graph project that aligns with your interests.
- Identify an area where you can contribute, such as data collection, model development, or documentation.
- Contact the project maintainers and express your interest in contributing.
- Follow the project's contribution guidelines and submit your changes.
Knowledge Graph Modeling Project
Show steps
Develop a small-scale knowledge graph model for a specific domain or topic.
Show steps
- Choose a domain or topic of interest.
- Identify the key entities, relationships, and properties in your domain.
- Design and implement a knowledge graph model using an appropriate technology.
- Populate your knowledge graph with data.
- Query and explore your knowledge graph to demonstrate its functionality.
Mentor a Knowledge Graph Beginner
Show steps
Share your knowledge by mentoring someone new to the field of knowledge graphs.
Show steps
- Identify a beginner who is interested in learning about knowledge graphs.
- Set up regular meetings or communication channels for mentoring.
- Provide guidance, support, and resources to help the beginner develop their knowledge and skills.
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