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This course includes:

  • 3 hours on-demand video
  • 25 articles
  • 20 downloadable resources
  • Full lifetime access
  • Access on mobile and TV
IT & Software Other IT & Software Information Architecture

Practical Knowledge Modelling: Ontology Development 101

Capture machine-interpretable knowledge through ontology and semantic techniques
Bestseller
Rating: 4.5 out of 54.5 (729 ratings)
3,098 students
Created by Tish Chungoora
Last updated 8/2020
English
English
30-Day Money-Back Guarantee

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
Curated for the Udemy for Business collection

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

8 sections • 79 lectures • 3h 35m total length

  • Preview02:17
  • Preview04:00
  • Preview00:35
  • Preview01:16
  • Conclusion
    00:41

  • Preview04:32
  • Data, information and knowledge
    02:41
  • What is a knowledge model?
    04:01
  • Ontology from a philosophical perspective
    02:16
  • Building blocks of a knowledge model
    05:13
  • Representing knowledge models
    02:27
  • Ontology from a logic based perspective
    04:05
  • Levels of abstraction in knowledge modelling
    05:26
  • Applications of knowledge modelling: Part 1
    02:46
  • Applications of knowledge modelling: Part 2
    02:18
  • Conclusion
    01:13

  • Overview
    04:34
  • Requirements management
    05:03
  • Goal and scope definition
    05:03
  • Competency questions
    02:09
  • Information gathering and elicitation
    04:26
  • Collating the preliminary information
    03:15
  • Conclusion
    01:03

  • Overview
    02:14
  • Listing and analysing statements
    05:07
  • Tracking and monitoring terms
    04:56
  • Graphical languages for knowledge modelling
    03:00
  • Unified Modelling Language: Part 1
    02:06
  • [Tutorial] Unified Modelling Language: Part 2
    04:51
  • [Tutorial] IDEF5 schematic language
    04:26
  • More thoughts on visual knowledge models
    02:21
  • Conclusion
    00:51

  • Overview
    03:25
  • [Tutorial] Getting started
    03:26
  • [Activity] Getting started
    00:39
  • [Tutorial] OWL classes: The basics
    03:30
  • [Tutorial] OWL classes: The basics (continued)
    03:10
  • [Activity] OWL classes
    00:40
  • [Tutorial] OWL individuals: The basics
    02:43
  • [Activity] OWL individuals
    00:18
  • [Tutorial] OWL properties: The basics
    03:17
  • [Tutorial] OWL properties: Domain and range
    03:09
  • [Tutorial] OWL properties: Inverse properties
    02:06
  • [Tutorial] OWL properties: Characteristics
    03:32
  • [Activity] OWL properties
    00:46
  • [Tutorial] Class description and definition: the basics
    02:21
  • [Tutorial] Existential restrictions
    03:42
  • [Activity] Existential restrictions
    00:45
  • Preview04:32
  • [Activity] hasValue restrictions
    00:59
  • [Tutorial] Primitive and defined classes
    04:41
  • [Activity] Primitive and defined classes
    00:16
  • [Tutorial] Reasoning in OWL
    05:44
  • [Activity] Reasoning in OWL
    00:53
  • [Tutorial] Universal restrictions
    03:30
  • [Activity] Universal restrictions
    00:26
  • [Tutorial] Cardinality restrictions
    02:41
  • [Activity] Cardinality restrictions
    00:32
  • [Tutorial] OWL properties: Datatype properties
    04:12
  • [Activity] Datatype properties
    00:50
  • [Tutorial] More on class description and definition
    04:54
  • [Activity] More on class description and definition
    00:28
  • [Tutorial] Other useful features
    06:04
  • [Activity] Other useful features
    00:30
  • Conclusion
    01:23

  • Overview
    02:44
  • [Tutorial] Ontology documentation
    01:57
  • [Tutorial] Ontology visuals: Part 1
    02:49
  • Ontology visuals: Part 2
    04:14
  • Ontology driven systems
    03:27
  • Conclusion
    00:32

  • Evaluating the effectiveness of ontologies
    03:02
  • Lessons learnt in ontology development and deployment
    01:48
  • Things to watch out for during ontology development
    02:50
  • Conclusion
    00:18

  • Conclusion
    02:23
  • [Bonus] Ontology reuse
    05:14
  • [Bonus] Useful skills for the knowledge architect
    02:21
  • Acknowledgements and more
    00:28

Instructor

Tish Chungoora
Ph.D. | CSPO
Tish Chungoora
  • 4.3 Instructor Rating
  • 4,447 Reviews
  • 22,937 Students
  • 8 Courses

I am a seasoned technology consultant with a passion for empowering people to apply best-in-class tools and techniques for professional development. My key experience is in knowledge graph technologies, product management, business analysis and technical publications.

I have a Ph.D. in systems & knowledge engineering and an extensive background in product design engineering. My innovative works in these areas have featured in over a dozen articles published in leading journals and conferences.

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