gangemi, fisseha, keizer, taconet, pettman, pisanelli: a merged fishery ontology for semantic...

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 Gangemi1, Frehiwot Fisseha2, Johannes

Keizer2, Marc Taconet4, Ian Pettman3, Domenico M. Pisanelli1

1 Institute of Cognitive Sciences and Technology, CNR (National Research Council), Rome, Italy {gangemi,pisanelli}@ip.rm.cnr.it, http://ontology.ip.rm.cnr.it2 FAO-GILW, Rome, Italy {Frehiwot.Fisseha,Johannes.Keizer}@fao.org, http://www.fao.org3 One Fish, SIFAR, Grange-over-Sands, Cumbria, UK, [email protected], http://www.onefish.org3

4 FIDI, FAO, Rome, Italy, [email protected], http://www.fao.org

mailto:Johannes.Keizer%[email protected]

mailto:[email protected]







An example of interoperability

• Trockenbeerenauslese

• late collection of grapes &• infected by botrytis cinerea

axiomatization axiomatization

• Muffato della Sala

roquefort cheese

compatible with


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


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


Ontology Merging Guidelines

Basic steps in the ONIONS/OntoClean Methodologies

DesignLibrary

Architecture

Deconstruct ExistingSources

Collect|integ.Ontology

DevelopmentResources

Create andDecompose

Glosses

AxiomatiseOntologyElements

Refine Informal

Relationships

Refine Taxonomy,

Define Rules

LexicaliseOntologyElements

Opt: MapReused

Ontologies

RefineLibrary

DecomposeTerms into

DependencyStructures

Assign Term Meaning to

OntologyElements

Assign OCT Taxonomical

Position & Meta-property

Iterate forNew Elementsfrom Glosses


Preliminary fisheries ontology library

Domain ontologies

Representationontology

Upperontology

Coreontology

Geographicontology

Speciesontology

Institutionsontology

Fishingdevicesontology

Fishing andfarming

techniquesontology

Farmingsystemsontology

Fisheryregulationsontology

Fisherymanagement

ontology

BiologicalontologyDevices

ontology

Legalontology Management

ontology

external theories:


oneFish topic trees (worldviews)

Administration

Subjects Ecosystem

Geography Species

Stakeholders


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)


Aquaculture in AGROVOC


Aquaculture in ASFA

Aquaculture

BrackishwaterAquaculture

MarineAquaculture

AquacultureDevelopment

AquacultureFacilities

BROADERTERM

BROADERTERM

RELATEDTERM

RELATEDTERM

FreshwaterAquaculture

AquacultureEconomics

AquacultureEngineering

BROADERTERM

RELATEDTERM

RELATEDTERM


Aquaculture in oneFish

Aquaculture

AquacultureEconomics

AquaculturePlanning

Subject

AquacultureDevelopment

SUBTOPICSUBTOPIC

SUBTOPIC

SUBTOPIC


Aquaculture in FIGIS (composites)

Aquaculture Resource

Water Area

land

strains

Specieslife 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


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


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


The APO schema

Activity

:Occurrence

1 PARTICIPANT nnnnnn Object

:Entity

1

METHOD

nnnnnn Plan

:MentalObject

(composed)1

INVOLVED-IN

nnnnnn


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!


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


APO applied to transactions

Transaction

:Occurrence

1 PARTICIPANT nnnnnn Customer

:Social Object

1

METHOD

nnnnnn Contract

:Information Object

(composed)1

INVOLVED-IN

nnnnnn


OCT: the OntoClean Top-level

Phenomenon

SpeConstDep:Object

Activity

GenConstDep:AbstractObject

Quality

EnduringSpeConstDep:EntityInhere-To:Entity

Quality Region

EnduringAlwaysPresent

Social Object

GenConstDep:Community

Mental Object

GenConstDep:SingularPerson

Abstract Object

NOT(Inhere:Location)GenConstDep:PersonMereoVariable

Arbitrary Collection

Pseudo-constantPart:Essential whole

Physical Object

Inhere:SpatialLocationNOT(Inhere:TemporalLocation)NOT(SpeConstDep:Object)

Occurrence

PerduringParticipant:ObjectInhere:TemporalLocationNOT(Inhere:SpatialLocation)[ALL]Temporal-Part:Occurrence[ALL]SpatialPart:Occurrence

Feature

Host:EntityEssential WholeHeterogeneous UnityGenConstDep:Entity

Object

EnduringEssential WholeHeterogeneous UnityParticipatesIn:Occurrence

Relational S

[EX>1]Participant:Object

Non-Relational S

[EX1!]Participant:Object

Entity

Process

Weakly-Homeomeric

Accomplishment

NOT(Homeomeric)

State

Homeomeric

Body

MereoInvariant

Ordinary Object

MereoVariable

Amount of Matter

MereoInvariant

Aggregate

EnduringNOT(Essential Whole)

Relevant Part

Part-Of:*Host

Place

NOT(Part-Of:*Host)


A core ontology for aquaculture

1

GENERICALLY-LOCATED

111111

nENFORCED-BY

111111

Institution

:Legal Person:Social Object

1TARGET

nnnnnn

MANAGED-BY

nnnnnn

Aquaculture

:Fishery:Activity

Geographic Area

:Spatial Location:Quality

1 SITUATED111111

Environment

:Physical Place

Water Area1SPATIALLY-LOCATED 111111

Aquaculture Management System

:Social Object

Regulation

:Plan

nnn1 REGULATED-BY nnn

1

MEMBER

nnnnnn

nnn

nnnnnn

nnn

1

METHOD

nnnnnn

Fish Farming Technique

:Technique:Plan

Aquatic Organism

:Biological Object

Aquaculture Resource

:Biological Collection

Breeding TechniqueHatchery Technique

Health Monitoring TechniqueSpawning Technique


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)))


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


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.


Web sites

• CNR site with methodology papers and example ontologies: http://ontology.ip.rm.cnr.it

• Agriculture Ontology Service site: http://www.fao.org/agris/aos

• Forthcoming fishery ontology site

http://ontology.ip.rm.cnr.it/



http://www.fao.org/agris/aos




Metadata types in ontology development resources

111

as reusable component

Documentation

Taxonomy

Lexical item

Topic

Informal domain ontology

InformalAxioms

Set of assertions

n EXTRACTED-FROM

111

Library of modules

Source

Set of axioms

Fishery resource types::Ontological structure

Ontological structure

Informal ontology fragment

RT informal axioms

Reusable component from original

Thesaurus

BT,NT,RT informal axioms

Glossary

Documentation

Topic tree

Inclusion hierarchies

Domain schema (conceptual template)

(Informal) axioms

Upper ontology

OntologicalStructureTopics namespace

Assertion

Individuals namespace

Relations namespace

ConceptConcepts namespace

Relation

Individual

Axiom

Set of lexical items

111

Processed namespace

n

EXTRACTED-FROM

111

Ontology element

BT/NT hierarchy

Topic tree fragment

Resource for ontology development

gangemi, fisseha, keizer, taconet, pettman, pisanelli: a merged fishery ontology for semantic...

Documents

merged fishery ontology

ontology development

ontologybased catalogue

farming techniques ontology

frehiwot fisseha

ian pettman

johannes keizer

marc taconet