1. Gangemi, Fisseha, Keizer, Taconet, Pettman, Pisanelli: A Merged Fishery Ontology for Semantic Interoperability The definition of a formal ontological framework aimed at semantic interoperability: the case for fisheries domain Aldo Gangemi 1, Frehiwot Fisseha 2, Johannes Keizer 2, Marc Taconet 4, Ian Pettman 3, Domenico M. Pisanelli 1 1 Institute of Cognitive Sciences and Technology, CNR (National Research Council), Rome, Italy {gangemi,pisanelli}@ip.rm.cnr.it, http://ontology.ip.rm.cnr.it 2 FAO-GILW, Rome, Italy {Frehiwot.Fisseha,Johannes.Keizer}@fao.org, http://www.fao.orgJohannes.Keizer}@fao.org 3 One Fish, SIFAR, Grange-over-Sands, Cumbria, UK, ip@ceh.ac.uk, http://www.onefish.org 3ip@ceh.ac.uk 4 FIDI, FAO, Rome, Italy, Marc.Taconet@fao.org, http://www.fao.orgMarc.Taconet@fao.org

2. Gangemi, Fisseha, Keizer, Taconet, Pettman, Pisanelli: A Merged Fishery Ontology for Semantic Interoperability An example of interoperability Trockenbeerenauslese late collection of grapes & infected by botrytis cinerea axiomatization Muffato della Sala roquefort cheese compatible with

3. Gangemi, Fisseha, Keizer, Taconet, Pettman, Pisanelli: A Merged Fishery Ontology for Semantic Interoperability Semantic interoperability of terminology-based systems Different fishery thesauri, taxonomies, topic trees  Different conceptualizations (current state)  Heterogeneous search results from multiple queries  Integrated conceptualizations (info brokering solution)  Union of results from one query engine (?homogeneity? depends on amount of analysis performed) Merged fishery ontology  Merged conceptualizations (formal ontology solution)  Union of more precise (homogeneus) results from one query engine  Conceptual navigation, custom user profiles, community knowledge sharing, ontology-based catalogue

4. Gangemi, Fisseha, Keizer, Taconet, Pettman, Pisanelli: A Merged Fishery Ontology for Semantic Interoperability Resources for the fishery ontology merging project 10,600 thesarus “descriptors” (Agrovoc, ASFA) 1,800 topic tree “subjects” (OneFish) 200 core “composite concepts” (FIGIS) 30,000 (≈taxonomical) “objects” (FIGIS)  Ontology Integration Framework  ONIONS merging methodology  OntoClean upper-level ontology

5. Gangemi, Fisseha, Keizer, Taconet, Pettman, Pisanelli: A Merged Fishery Ontology for Semantic Interoperability Ontology Merging Guidelines Basic steps in the ONIONS/OntoClean Methodologies Design Library Architecture Deconstruct Existing Sources Collect|integ. Ontology Development Resources Create and Decompose Glosses Axiomatise Ontology Elements Refine Informal Relationships Refine Taxonomy, Define Rules Lexicalise Ontology Elements Opt: Map Reused Ontologies Refine Library Decompose Terms into Dependency Structures Assign Term Meaning to Ontology Elements Assign OCT Taxonomical Position & Meta-property Iterate for New Elements from Glosses

6. Gangemi, Fisseha, Keizer, Taconet, Pettman, Pisanelli: A Merged Fishery Ontology for Semantic Interoperability Preliminary fisheries ontology library Domain ontologies Representation ontology Upper ontology Core ontology Geographic ontology Species ontology Institutions ontology Fishing devices ontology Fishing and farming techniques ontology Farming systems ontology Fishery regulations ontology Fishery management ontology Biological ontology Devices ontology Legal ontology Management ontology external theories:

7. Gangemi, Fisseha, Keizer, Taconet, Pettman, Pisanelli: A Merged Fishery Ontology for Semantic Interoperability oneFish topic trees (worldviews) Administration SubjectsEcosystem GeographySpecies Stakeholders

8. Gangemi, Fisseha, Keizer, Taconet, Pettman, Pisanelli: A Merged Fishery Ontology for Semantic Interoperability What is being done for fast prototyping a FOS-based system (1) Choosing and installing an ontology server Translating the most conceptually transparent portions of the resources into formal logic-based languages Building a preliminary core-level ontology wrt OCT upper ontology and FIGIS composite concepts Cleaning ontology building data to populate domain ontologies (next slide)

9. Gangemi, Fisseha, Keizer, Taconet, Pettman, Pisanelli: A Merged Fishery Ontology for Semantic Interoperability Aquaculture in AGROVOC

10. Gangemi, Fisseha, Keizer, Taconet, Pettman, Pisanelli: A Merged Fishery Ontology for Semantic Interoperability Aquaculture in ASFA

11. Gangemi, Fisseha, Keizer, Taconet, Pettman, Pisanelli: A Merged Fishery Ontology for Semantic Interoperability Aquaculture in oneFish

12. Gangemi, Fisseha, Keizer, Taconet, Pettman, Pisanelli: A Merged Fishery Ontology for Semantic Interoperability Aquaculture in FIGIS (composites) Aquaculture Resource Water Area land strains Species life cycle Farming system management system Production center Spawning technique Breeding technique Hatchery technique Expl. form Regulation Farming technique Environment Institution Health monitoring technique diseases suppliers

13. Gangemi, Fisseha, Keizer, Taconet, Pettman, Pisanelli: A Merged Fishery Ontology for Semantic Interoperability FOS development (2) BT/NT are transformed into taxonomies; e.g.: SUBSUMES(c1,c2), provided that c1 \ c2 according to upper ontology? RT are transformed into axioms; e.g.: PARTICIPANT(i1,i2), provided that the topmost parents of c1(i1) and c2(i2) are related by PARTICIPANT in the core ontology? Topic trees into (preliminary) topic spaces

14. Gangemi, Fisseha, Keizer, Taconet, Pettman, Pisanelli: A Merged Fishery Ontology for Semantic Interoperability Conceptual templates Conceptual templates are relevant parts of ontologies that describe the core concepts and relations of a domain (core ontologies) Ex. APO, BFQF, etc. They can be often discovered from: database schemata, forms, elicited know-how analysis of systematic polysemy

15. Gangemi, Fisseha, Keizer, Taconet, Pettman, Pisanelli: A Merged Fishery Ontology for Semantic Interoperability The APO schema Activity :Occurrence 1 PARTICIPANT nnnnnn Object :Entity 1 METHOD nnnnnn Plan :MentalObject (composed) 1 INVOLVED-IN nnnnnn

16. Gangemi, Fisseha, Keizer, Taconet, Pettman, Pisanelli: A Merged Fishery Ontology for Semantic Interoperability Use of APO It resulted useful in several domains: clinical guidelines (planning vs. process knowledge) fishery (management vs. intervention knowledge) banking regulations (legal vs. world knowledge) possibly extendable to the general problem of control knowledge In the third lecture some examples from the banking domain will be given Warn the mereotopological constraints when applying it!

17. Gangemi, Fisseha, Keizer, Taconet, Pettman, Pisanelli: A Merged Fishery Ontology for Semantic Interoperability The APO schema modified for clinical conditions Condition :Occurrence 1 PARTICIPANT nnnnnn Bio.Object :Object 1 REPRESENTED-BY nnnnnn Finding :MentalObject (composed) 1 INVOLVED-IN nnnnnn

18. Gangemi, Fisseha, Keizer, Taconet, Pettman, Pisanelli: A Merged Fishery Ontology for Semantic Interoperability APO applied to transactions Transaction :Occurrence 1 PARTICIPANT nnnnnn Customer :Social Object 1 METHOD nnnnnn Contract :Information Object (composed) 1 INVOLVED-IN nnnnnn

19. Gangemi, Fisseha, Keizer, Taconet, Pettman, Pisanelli: A Merged Fishery Ontology for Semantic Interoperability OCT: the OntoClean Top-level

20. Gangemi, Fisseha, Keizer, Taconet, Pettman, Pisanelli: A Merged Fishery Ontology for Semantic Interoperability A core ontology for aquaculture

21. Gangemi, Fisseha, Keizer, Taconet, Pettman, Pisanelli: A Merged Fishery Ontology for Semantic Interoperability An excerpt from the ontology The concept fishing technique is formalized in a description logic as follows: (defconcept Fishing-Technique :annotations ((DOCUMENTATION "FIGIS: A fishing technique describes the set of equipment used for the capture of a target species together with any associated fishing practices.")) :is (:and Technique (:some INVOLVES Gear) (:some METHOD-OF Fishery) (:some PART Handling-Mode)))

22. Gangemi, Fisseha, Keizer, Taconet, Pettman, Pisanelli: A Merged Fishery Ontology for Semantic Interoperability FOS development (3) Producing or reusing glosses (informal descriptions) Building and refining library architecture Choosing integration architecture (mediation or merging) Applying integration, building and active cataloguing procedures Building (or reusing) query interface and wrappers to source dbs

23. Gangemi, Fisseha, Keizer, Taconet, Pettman, Pisanelli: A Merged Fishery Ontology for Semantic Interoperability Fisheries merged information access A user query is submitted to an interface connected to the Fishery Ontology Server. Interface and Server communicate with a Topic-Based Fishery Information Browser. The browser can either interrogate the source systems, or perform own searches to document corpora. The Server can directly provide information on fishery conceptual structures, terminology, and scope notes.

24. Gangemi, Fisseha, Keizer, Taconet, Pettman, Pisanelli: A Merged Fishery Ontology for Semantic Interoperability Web sites CNR site with methodology papers and example ontologies: http://ontology.ip.rm.cnr.itCNR site with methodology papers and example ontologies: http://ontology.ip.rm.cnr.it Agriculture Ontology Service site: http://www.fao.org/agris/aosAgriculture Ontology Service site: http://www.fao.org/agris/aos Forthcoming fishery ontology site

25. Gangemi, Fisseha, Keizer, Taconet, Pettman, Pisanelli: A Merged Fishery Ontology for Semantic Interoperability Metadata types in ontology development resources