The Semantic Web Week 17 Knowledge Engineering – Real Example: Accuracy of Ontologies Module Website: Practical this week: Using the Student CPS

FAROAS - A Case Study involving Aircraft Separation Criteria Shanwick Oceanic Area segment1 segment2

Recap - Looking at the “Formal Specification of an Conceptualisation” of an Air Traffic Control world – A Real Example - Language used for the specification – customised, many-sorted first order logic

Dichotomy General Languages (OWL) with General Tools (Protégé) “One size fits all” - Can spend a great deal of effort on (re-usable) tool support - Can share the products – the ontologies - Can make tools so that they can ‘configure’ to be more suited to specific applications BUT - In some (many) cases they might be useless – they might not ‘fit’ the application or might not be expressive enough - They might come with lots of baggage that is NOT required in an application

Dichotomy Customised Language and tools for each application (ATC example) n Can choose them and shape them to be ‘semantically close’ to the application (make sure they don’t include excess baggage) n Their expressiveness can be chosen to fit the problem BUT n Tools must be written / acquired n Exporting / sharing ontology not easy HOWEVER: n Can create powerful, specific acquisition and maintenance tools (as in the ATC example…)

The Student CPS The ATC ontology is called the “CPS” – conflict prediction specification n I have created a “Student CPS” - about 10% of the CPS n The Student CPS can be used to show all the features present in the CPS and its tools environment!

Increasing the quality of a (Complex) Ontology An ontology may have errors in the form of: - Type 1. Non-well formed parts - Type 2. Incorrect parts - Type 3. Incomplete parts - Type 4. Inaccurate parts

Increasing the quality of a (Complex) Ontology - Syntax / phrase structure/ type check – Type 1 - Validation form – Mainly Type 2 - Execution form - Types 2,3,4 - Batch tests - Property checks / inconsistency - Simulation - Other tools eg automated maintenance

Conclusions - Certain knowledge can be acquired and shared in an inaccurate form – eg WORDNET or Pizza – type applications - Certain knowledge must be acquired and maintained in an accurate form – eg ATC-type application, legal information, travel information, control information… - In the latter case we need the help of more elaborate tools than Protégé-2000