UNCLASSIFIED Taxonomy and Ontology Ian Bailey

UNCLASSIFIED Overview Attempt to compare the disciplines of Taxonomy and Ontology – What do they have in common ? – Where do they differ ? – How are they used ? Case Study: UK Defence Taxonomy – In March 2009, MOD ran a small research project to investigate how master reference data is best provided to enterprise architects – We took the UKDT and re-engineered large parts of it into a formal ontology (based on IDEAS ontology) Assume the audience knows far more about Taxonomy than I do

UNCLASSIFIED Taxonomy and Ontology Several definitions for both, not all of them are consistent The types of taxonomy developed in UK Gov seem to be about terminology – Providing consistent terms to enable better discovery of information and consistency of communication – Usually implemented in software systems, but their goal is to help humans find stuff and be more consistent Again, there are different flavours of ontology around – They all seem to share the common trait of being models of domain of interest – Unlike a taxonomy, an ontology models the things of interest and their relationships. The names of those things is of secondary concern to the structure of the things – Ontologies tend not to be for human consumption – not only are they “computer-interpretable”, they are generally speaking able to configure a system to do certain things

UNCLASSIFIED T&O – Quick Example to Compare Barracks and garrisons taxonomy – Descending by “narrower term” – Aldershot Garrison narrower than Barracks and Garrisons – Arnhem Barracks Aldershot narrower than Aldershot Garrison An ontology cares more about the nature of these things Barracks and Garrisons is a type Aldershot Garrison is and individual Their relationship is type-instance Arnhem Barracks is also an individual Its relationship to Aldershot Garrison is whole-part Making these distinctions allows for computer systems to interpret reality in a way that is closer to human understanding

UNCLASSIFIED Looking at it Another Way Venn Diagrams & Physical Structures – Types (ovals) and Individuals (rectangles) – Individuals and their parts Relationships are important – What was simply narrower term in the taxonomy breaks down into super-subtype (between types), type-instance (between types and things of that type) and whole-part (between individuals) built estate barracks and garrisons Aldershot garrison Arnhem Barracks, Aldershot Aldershot garrison Arnhem Barracks Browning Barracks Brunevel Barracks etc. super-subtype type-instance whole-part

UNCLASSIFIED Why Bother ? This may seem like a lot of fuss… However, you can build systems on this stuff Super-Subtype Inheritance – If we know Built Estate has a lat-long location, then we know Barracks and Garrisons also have lat-long Type-Instance – …and we also know that Aldershot has a specific lat-long value Whole-Part – If we know Aldershot Garrison is in Hampshire then we know Brunevel Barracks is also in Hampshire The point is that a certain degree of sophistication is required in order that systems can make inferences that can support business – Allows automation of a number of processes that would otherwise have been manual

UNCLASSIFIED Names & Objects There are things in the real word (individuals, types, relationships) and there are the names we give them Name SpaceObject Space Built Estate Aldershot garrison Barracks and Garrisons Arnhem Barracks, Aldershot super-subtype type-instance whole-part named-by narrower-term Ontologies tend to become quite “webby”, and this is a good thing. It better reflects reality, is extensible, and can cope with very complex concepts

UNCLASSIFIED Synonyms and Homonyms The next level of sophistication for on ontology is to allow more than one namespace – Each object in the real world may have more than one name, each belonging to different namespaces – e.g. German, French and English names: – Homonyms are simply the same text being use to describe two different objects, but in two different namespaces German Namespace French Namespace English Namespace “Hund” “chien” “dog” named-by Army Namespace RAF Namespace Navy Namespace “tank” named-by

UNCLASSIFIED Take Care with Synonyms Some taxonomies can be quite loose with their “Alternative Terms” – Prime Minister <> Tony Blair – Recycling <> Black Bin Bag Sometimes, what appear to be synonyms are actually names applying to different states of something: Person Time “Miss A Smith” “Mrs A Jones” “Miss A Smith” “Mrs A Evans” In the same way that we use whole-part to break individuals into their physical parts, we can also break them into temporal parts This is called 4D Ontology Each temporal part has a name

UNCLASSIFIED Methodology There aren’t many formal methods for developing ontologies – Either done by navel-gazing academics agonising for weeks over the essence of a concept – …or hacked together by programmers – Neither are ideal situations There is one methodology, designed for re- engineering existing data into an ontology – The BORO Method (Business Object Re-engineering Ontology) – Developed by Chris Partridge – ex KPMG legacy data practice lead – IDEAS upper ontology is developed using BORO

UNCLASSIFIED BORO Flowchart Select a concept for analysis Does it have spatial and temporal extent ? Does it have members ? no (not individual) Add to model yes (individual) yes (type) no Does it relate things ? yes (tuple) no (if you’ve got to this stage, the concept needs to be broken down further) what does it relate ? Add these things to the analysis yes what are the members ? Select some typical members and analyse these START HERE

UNCLASSIFIED Ontology in MOD – Country Codes Starting with the SCOPE geo taxonomy, we built an ontology for locations – Using the namespace concept, we allowed for multiple names and identifiers for each geo-political entity e.g. ISO country codes, NATO country codes, US FIPS10-4 country codes, names in English, German, etc. – Also added borders information whole-part type-instance named-by

UNCLASSIFIED Ontology in MOD – EA Master Data Enterprise Architecture is multidisciplinary – Business processes, org structures, systems modelling, etc. Need to encourage consistent terminology and structures in EA – Maximise re-use of existing architecture Used UK Defence Taxonomy as basis and produced an ontology for MODAF users – Defence Estates – bases, garrisons, barracks – Equipment – types of platform, weapon, comms system, etc. – Organisation structure – brigades, squadrons, etc. Also pulled in data from other sources – Defence Framework (org structure of MOD) – MOD website (military org structures)

UNCLASSIFIED Where We Are, Where We’re Going IDEAS – International upper ontology developed by defence ministries of UK, US, Canada, Sweden and Australia – Adopted by DoD as basis for DoD Architecture Framework v2.0 (DODAF DM2) – Foundation released in April 2009 UK MOD – Continued involvement with ontology and IDEAS – Michael Warner keeps tabs on projects – Currently investigating use of IDEAS in MODAF (as the US did with DoDAF) – Other ontology projects around – esp. around intelligence and counter-terror Ordnance Survey – John Goodwin at OS – Developing natural language notations for ontologies – Will present at a future TIPS event

UNCLASSIFIED Further Reading BORO & Ontology – Cutter Paper – Chris Partridge’s book “Business Objects: Re-Engineering for Re-Use” ISBN – 4D Ontology “How Things Persist”; Katherine Hawley ISBN

UNCLASSIFIED Contact Ian Bailey