1. Craigiebuckler, Aberdeen, AB15 8QH, UK Macaulay Modelling Team Work on Ontologies October 2005 – March 2006 Gary Polhill and Nick Gotts

2. Work On Ontologies: Summary Literature Survey Design work on FEARLUS 1-0 Socio-Techno-Ecosystems First Draft Domain Structure Ontology for CAVES Ontologies as CAVES “Mapping Tools”

3. Literature Survey (1): Application Areas Business applications “E-learning”: classifying/recommending papers/software Scientific domains Medicine, Bioinformatics Ecology (Link to STELLA) Food and Agriculture (FAO recommended to “Incrementally build a rich ontology of the FAO domain”) MAS “Superdomains” Geospatial information Processes

4. Literature Survey 2: Languages and Formalisms Three species of OWL (OWL-Lite, OWL-DL, OWL-Full) Description Logics (SHIQ and variants) RDF (“Resource Description Framework) and RDF Schema (RDFS) XML Other Areas F-Logics Ontology-Composition Algebras Alternative syntaxes for OWL, RDFS Spatial, temporal, spatio-temporal logics

5. Literature Survey 3: Ontology Learning Sources: Structured input: databases, web pages, machine- readable dictionaries or thesauri Free text Often start with initial ontology or key terms Natural language processing software used to identify terms for concepts, constructions that indicate relationships between concepts Taxonomic relations much easier to identify than others General agreement: full automation a long way off

6. Literature Survey 4: Upper-Level Ontologies OpenCyc (subset of Cyc) Remains proprietary SUMO Aims to be IEEE standard Something of a “ragbag” DOLCE No single “right” ontology Aims at isolating the “fundamental ontological options” Start of attempt to provide a range of “foundational ontologies”

7. Literature Survey 5: The OntoClean Methodology Particulars and universals Extension and intension Essence and “Rigidity” Identity criteria Unity: criteria of “wholeness” Avoiding overuse of subsumption: the statue and the clay

8. CAVES Upper Ontology: Top Levels Particular Endurant (roughly, something that endures) Physical Endurant AmountOfMatter PhysicalThing Feature Non-physical Endurant: MentalThing SocialThing Agent (overlaps both Physical Endurant and Non- physical Endurant) Perdurant (state, event, process, action…) AgentivePerdurant NonAgentivePerdurant Location (in space, time, conceptual space) Abstract (something with no spatio-temporal location)

9. CAVES Upper Ontology: PhysicalThing PhysicalObject (“something you can pick up and throw”) LivingThing NonHumanOrganism DomesticAnimal CropPlant HumanBeing NonLivingPhysicalObject FieldOfCrop (a conglomeration of PhysicalObjects and AmountOfMatters) HerdOfAnimals (note: can remain the same herd while individual animals come and go)

10. CAVES Upper Ontology: SocialThing ImpersonalSocialThing Law, Language, Currency, Ritual… SocialFormation SocialNetwork KinshipNetwork, FrienshipNetwork… Organisation Class, EthnicGroup… SocialRole FormalSocialRole Husband, Landlord, Chief… InformalSocialRole Friend, RoleModel…

11. CAVES Upper Ontology: Abstract NetworkThing Network Tree DirectedNetwork UndirectedNetwork Node Link DirectedLink UndirectedLink Clique Procedure (something like a recipe) LandUseProcedure VeterinaryProcedure

12. Successor to FEARLUS (Dubbed fearlus 1-0) Based on four ontologies –Domain Structure –Framework –Scenario –Model Two states of the world (expressed as OWL instances) –Input –Output Strengthening link between evidence and model Design submitted to WCSS-2006 Scenario Domain Structure Framework Model Equivalence Import & Subclass Import Simulation Real World OutputInput

13. Ontologies as a Coordination Tool in CAVES: Next Steps Complete draft Domain Structure Ontology Further investigate ontology generation tools and methods Produce FEARLUS 1-0 ontology Apply selected tools/methods to case study and model materials Refine existing case study ontologies Produce ontologies of Odra, Queensland case studies Produce ontologies of prototype models? Major constraint: Macaulay modelling team’s time!