Practical Knowledge Modelling: Ontology Development 101
What you'll learn
- Become better at approaching the organization of information and knowledge in such a way that it makes sense to users
- Apply a methodology for developing seamless knowledge models (ontologies) and use that understanding across any subject matter
- Gain awareness of the inner workings of knowledge models (ontologies) expressed as visual and machine-interpretable representations
- Develop semantically-rich ontologies and knowledge graphs, formalized in the Web Ontology Language (OWL), using the Protégé ontology editor
Requirements
- Diagramming tool for drawing shapes, e.g. Microsoft Office Visio, yEd, Draw io, Lucidchart, UML design tools, etc., or simply pen and paper
- Protégé desktop ontology editor (please do not download until we have reached Section 5)
- Spreadsheet application, e.g. Microsoft Office Excel or similar
Description
Ever wondered how you could capture and represent knowledge to share it with someone else, using the most efficient way possible? Are you interested in learning how knowledge can be pieced together for human interpretation and Artificial Intelligence?
Chances are we've probably all at some point been faced with situations where we wished there was a quicker, more effective, way of capturing and representing knowledge so that it makes sense to human beings and computers. Knowledge modelling (or technically speaking, ontology modelling) is about the tools and techniques for capturing and representing knowledge. A knowledge model (a.k.a. ontology) is, basically, a representation that provides a basis for sharing meaning about some subject matter.
There are a great many uses of knowledge modelling from Artificial Intelligence to the Semantic Web, natural language processing, controlled vocabularies, reference models used in business analysis, engineering and heaps more. In this course, you'll learn how to go about modelling knowledge from a practical perspective, which means that in addition to getting an appreciation of the context of knowledge modelling, you'll also be expected to get your hands dirty! So, we'll be looking at applying different methods for understanding how to compose knowledge models. These methods include graphical as well as formal computer-aided techniques.
This course is for people who care about knowledge sharing and making knowledge a true asset to support knowledge management, systems interoperability, intelligent information architecture, best practice knowledge capture, and many more.
Who this course is for:
- People with an interest in knowledge sharing
- People with a willingness to learn machine-interpretable methods for capturing knowledge
- Individuals who operate in areas like information and knowledge management, business analysis, enterprise architecture, information systems, etc.
- Professionals who intend to work with knowledge graph technologies, graph databases and similar NoSQL technologies
- The course does not cover advanced ontology engineering, ontology theory and mathematical logic
Course content
- Preview02:17
- Preview04:00
- Preview00:35
- Preview01:16
- 00:41Conclusion
Instructor
![Tish Chungoora](data:image/svg+xml,%3Csvg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64"%3E%3C/svg%3E){kind=avatar}
- 4.3 Instructor Rating
- 5,839 Reviews
- 29,033 Students
- 9 Courses
I am a seasoned technology professional with a passion for empowering people to apply innovative and best-in-class approaches targeted at information architecture, product management, business analysis and technical publications.
As a bestselling online instructor, one of my goals is to advocate for knowledge graph technology in order to augment enterprise data architecture, promote systems interoperability and extend product lifecycle management capabilities.
I have a Ph.D. in systems & knowledge engineering and an extensive background in product design engineering.