Course Description
A “Business Ontology” defines a common set of unambiguous concepts, that are central to your business. Getting everyone on the same page improves search and facilitates harmonization of data repositories. Complexity is greatly reduced, allowing for more flexible evolution of enterprise systems. Designing and Building Business Ontologies will help give you the edge you need to transform your information systems. Does this sound like you? - My information systems are bogged down and I’m not sure which way to turn. - I get that semantic technology can help, but don’t know how to proceed. - What’s the big deal about triples and linked data? - What’s the difference between an ontology and a data model? - How can I use OWL, if I am used to object-oriented modeling? - I’m digging the ideas about logic &inference, but don’t know how it works. - I know the basics of OWL, but I want more advanced material. - I want to build industry-strength ontologies. - I like to have FUN while I learn. This course is far more than learning the syntax of the Semantic Web or how to use tools to implement semantic based systems (although it certainly does cover both of those). This course is about learning how to think and design in semantics. We have been continually evolving this course over the ten years we have been teaching it. We are always adding new technologies and new techniques to the course. Over the course of time we’ve learned how students learn this new material and have continued to adopt the course materials. ***Discounts are available for bulk registration. Please inquire for details.***
What am I going to get from this course?
General:
- Describe where semantic technology has made a difference in industry today.
- Identify opportunities and challenges in your organization that can be addressed by semantic technology.
- Continue your education by self-learning.
- Evangelize the importance of joining the data-centric revolution.
- Understand and describe the advantages of a graph database over traditional relational databases, with reference to URIs and triples.
- Understand and describe the importance of having an enterprise ontology in the organization, and why it should be based on an upper ontology.
- Explore publicly available ontologies and triple stores from SPARQL endpoints.
- Represent and query knowledge and data in a triple store using OWL, RDF & SPARQL.
- Leverage the benefits of having the schema and the data in the same store.
- Extract data from a relational database in the form of triples using the W3C standard mapping languaage: R2RML.
- Use RDF Shapes (SHACL) to manage constraints on how the ontology may be used in an application.
- Use modern software tools to build and leverage core components of enterprise ontologies using a proven method based on using gist, an upper enterprise ontology.
- Avoid common errors that result in overly complex ontologies. This entails judicious choices of when to create new classes and properties.
- Build an ontology that is both a conceptual model of the subject area as well as being directly usable as a data schema in a triple store.
- Divide up an ontology into modules using the ontology import mechanism.
- Understand how inference is used for represented enterprise knowledge and also how it can be used to help debug your ontology.