UNCLASSIFIED

deasgroupi

Taxonomy and Ontology

Ian Baileyian@modelfutures.com

UNCLASSIFIED

deasgroupiOverview• 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

deasgroupiTaxonomy 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

deasgroupiT&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

deasgroupiLooking 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 BarracksBrowning BarracksBrunevel Barracksetc.

super-subtype

type-instance whole-part

UNCLASSIFIED

deasgroupiWhy 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

deasgroupiNames & 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

type-instance

whole-part

named-by

named-by

named-by

named-by

narrower-term

narrower-term

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

deasgroupiSynonyms 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-bynamed-by

named-by

Army Namespace

RAF Namespace

Navy Namespace “tank”

“tank”

“tank” named-by

named-by

named-by

UNCLASSIFIED

deasgroupiTake 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” “MrsA Jones” “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

deasgroupiMethodology• 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

deasgroupiBORO Flowchart

Select a concept for

analysis

Doesit 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

deasgroupiOntology 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

whole-part type-instance

named-by

UNCLASSIFIED

deasgroupiOntology 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

deasgroupiWhere 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

deasgroupiFurther Reading• BORO & Ontology– Cutter Paper• http://www.cutter.com/offers/forensicIS.html

– Chris Partridge’s book• “Business Objects: Re-Engineering for Re-Use” • ISBN 978-0955060304

– 4D Ontology• “How Things Persist”; Katherine Hawley• ISBN 978-0199275434

UNCLASSIFIED

deasgroupiContact

Ian Baileyian@modelfutures.com

www.modelfutures.com