Our methodology emphasizes hands-on practice using examples drawn from the real world. However, this hands-on training occurs in the context of a significant amount of theoretical background. It is important that our students grasp these concepts, so we ensure that all students get at least a quick review of the ideas used in their particular course, unless they have signed up for an advanced course where these fundamentals are specifically assumed.

• Elementary set theory
• Basics of topology and taxonomy
• The difference between declarative and imperative specification
• Review of query and transaction systems:  OLTP vs. OLAP, etc.
  
• Expert system basics, including backward/forward chaining
• Metadata fundamentals: resources, identifiers, statements, and reification
• Ontology fundamentals: classes, properties, individuals, restrictions, and entailment
  
• Understanding meta-classes and meta-properties
• Relationships between XML, RDF, RDFS, OWL-Lite, OWL-DL, OWL-Full, OWL 1.1
  
• System theory regarding networks of machines exchanging model data during computation
  
• Relationship between ontology, Web Service and BPM concepts
  

Hands on skill training is the core of what we teach. Note that not all of these skills are taught in every semantic skills tutorial.

Using all chosen tools:

• Manipulation of simple RDF/RDFS models.
• Using OWL to create more sophisticated knowledge models. GUI interfaces to inference, explanation, fancy features.
  
• Querying your models, locally and remotely, using any combination of SPARQL, Fresnel, and Peruser.
• Using rule engines to perform inference, and DIG reasoners to classify resources and derive entailed properties.
• Broad vision of power-assist lightweight knowledge apps in a mobile, connected universe.
  

Using relevant chosen tools, to degree of student interest:

• More technical depth on rule standards, integration, inference issues, SPARQL, DIG, Peruser, etc.
  
• Knowledge visualization techniques (not our specialty, but we have our favorites).
  
• Testing and validation of ontology models. Use of ontologies for system verification and compliance. (A big subject, and our specialty, so let us know in advance if this is an interest area for your team). 
  
• Application integration techniques (requires programming background) - e.g. integration of ontologies with web services and databases.
  
• Techniques for construction and maintenance of ontology library shelves. Sharing, merging and comparing models. Tomorrow's library.
  
• Tool configuration - tips and tricks

Numerous standards and languages are relevant to the content of some or all of our lessons. This does not imply that other standards and languages are not important or useful, and many others may be brought up in class discussion or examples.

• RDF (and RDFS)
  
• OWL 1.0 : OWL-DL, OWL-Lite, OWL-Full, as well as OWL 1.1
  
• Model queries: SPARQL, DIG, Fresnel
  
• XML Namespaces, XML Schema, XSLT, XPath, XQuery
  
• SVG, CSS and other nonstandard renderings, e.g. OpenLaszlo, AJAX, and Flash.
  
• RuleML,SWRL
• ebXML, BPEL
  
• Java, SQL, UML, XMI, SOAP, REST, WSDL, OASIS WS-*
  
• Common, important, and historic ontologies: RSS, Wordnet, SUMO, FOAF, Dublin-Core, DAML, Cyc, KIF
  
• TopicMaps are mentioned in passing.

The class is held in a teaching laboratory where each student has an assigned desktop PC with high-speed internet access. All tools used in the class are already installed and configured when students arrive.

Wi-fi access is also provided for those with laptops, although we request that students avoid distractions during instruction sessions.

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