Building a rich ontology from AGROVOC

Building a rich ontology from AGROVOC Dagobert Soergel College of Information Studies, University of Maryland [email_address] , www.dsoergel.com FAO Agricultural Ontology Server Workshop Beijing, April 27 - 29, 2004

The problem
AI and Semantic Web applications need full-fledged ontologies that support reasoning
Constructing such ontologies is expensive
While existing KOS do not provide the full set of precise concept relationships needed for reasoning, existing KOS, both large and small, represent much intellectual capital KOS = Knowledge Organization System
How can this intellectual capital be put to use in constructing full-fledged ontologies
Specifically: From AGROVOC to a full-fledged Food and Agriculture Ontology

Some applications of a Food and Agriculture Ontology
Advice on crops and crop management (fertilization, irrigation)
Advice on pest management
Tracking contaminants through the food chain
Advice on safe food processing
Computing nutrition labels
Advice on healthy eating
Improved searching

AGROVOC relationships compared with more differentiated relationships of a Food and Agriculture Ontology

Food and Agriculture Ontology AGROVOC Rule 1 Part X < mayContainSubstance > Substance Y IF Animal W < hasComponent > Part X AND Animal W < ingests > Substance Y Rule 2 Food Z < containsSubstance> Substance Y IF Food Z < madeFrom > Part X AND Part X < containsSubstance > Substance Y Differentiated relationships milk < includesSpecific> cow milk < containsSubstance > milk fat cows < hasComponent > cow milk* Cheddar cheese < madeFrom > cow milk Undifferentiated hierarchical relationships milk NT cow milk NT milk fat cows NT cow milk Cheddar cheese BT cow milk

From AGROVOC to FA Ontology
Define the FA Ontology structure
Fill in values from AGROVOC to the extent possible
Edit manually with computer assistance using the rules-as-you go approach and an ontology editor:
make existing information more precise
add new information

Define ontology structure Overall model

Concept Relationships between concepts Lexicalization/ Term String Relationships between strings Relationships between terms designated by manifested as Other information: language/culture subvocabulary/scope audience type, etc. annotation relationship Relationship Relationships between Relationships Note

Define ontology structure Relationship types

Inverse relationship Relationship Y < isa> X Y < inheritsFrom > X X <includesSpecific> X < inheritsTo > Y Isa

Inverse relationship Relationship Y < substanceContainedIn > X Y < ingredientOf > X Y <usedToMake> X Y < portionOf > X Y < spatiallyIncludedIn > X Y < componentOf > X Y < subprocessOf > X Y < memberOf > X Y X < containsSubstance > Y X < hasIngredient > Y X < madeFrom> Y X < yieldsPortion > Y X < spatiallyIncludes > Y X < hasComponent > Y X < includesSubprocess > Y X < hasMember > Y Holonymy / meronymy (the generic whole-part relationship)

Inverse relationship Relationship Y < causedBy > X Y < performedByInstrument > X Y < usesProcess > X Y < benefitsFrom > X Y < treatedWith > X Y < harmedBy > X Y < afflicts > X Y < growthEnvironmentFor > X Y < propertyOf > X Y < indicates > X Y < similarTo > X Y < oppositeTo > X Y <phase Of> X Y < ingestedBy > X Y < usedToMake > X X < causes > Y X < instrumentFor > Y X < processFor > Y X < beneficialFor > Y X < treatmentFor > Y X < harmfulFor > Y X < hasPest > Y X < growsIn > Y X < hasProperty > Y X < hasSymptom> Y X < similarTo > Y X < oppositeTo > Y X <hasPhase > Y X < ingests > Y X < madeFrom > Y Further relationship examples

Fill in values from AGROVOC
Fill in values from AGROVOC to the extent possible
Arrange in structured sequence (to the extent possible based on the information in AGROVOC) to facilitate editing (The editor can deal with similar problems at the same time.)

milk NT cow milk milk NT goat milk milk NT buffalo milk milk NT milk fat milk RT milk protein milk RT lactose cows RT cow milk goats RT goat milk ewes RT ewe milk goat milk RT goat cheese ewe milk RT ewe cheese acid soils BT chemical soil types acrisols BT genetic soil types alkaline soils BT chemical soil types aluvial soils BT lithological soil types chemical soil types BT soil types Cichorium BT Asteraceae Cichorium endivia BT Cichorium Cichorium intybus BT Cichorium Cichorium intybus RT coffee substitutes Cichorium intybus RT root vegetables blood NT blood protein blood NT blood lipids Edited relationships Undifferentiated relationships from AGROVOC

Edit manually with computer assistance
Use the rules-as-you-go approach and good ontology editing software that handles large ontologies efficiently
make existing information more precise
add new information
Assumption:
Entity types of concepts are known from AGROVOC or other sources (Langual, UMLS, WordNet); for example
milk fat is a Substance
Asteraceae is a taxon
The editor may need to determine the entity type

The rules-as-you-go approach Exploit patterns to automate the conversion process Example
1. An editor has determined that
milk NT cow milk should become milk < includesSpecific > cow milk
She recognizes that this is an example of the general pattern milk NT * milk  milk < includesSpecific > * milk (where * is the wildcard character)
Given this pattern, the system can derive automatically
milk NT goat milk should become milk < includesSpecific > goat milk
Result:

milk < includesSpecific > cow milk milk < includesSpecific > goat milk milk < includesSpecific > buffalo milk milk NT cow milk milk NT goat milk milk NT buffalo milk milk NT milk fat milk RT milk protein milk RT lactose cow RT cow milk goats RT goat milk ewes RT ewe milk goat milk RT goat cheese ewe milk RT ewe cheese acid soils BT chemical soil types acrisols BT genetic soil types alkaline soils BT chemical soil types aluvial soils BT lithological soil types chemical soil types BT soil types Cichorium BT Asteraceae Cichorium endivia BT Cichorium Cichorium intybus BT Cichorium Cichorium intybus RT coffee substitutes Cichorium intybus RT root vegetables blood NT blood protein blood NT blood lipids Edited relationships Undifferentiated relationships from AGROVOC

The rules as you go approach Exploit patterns to automate the conversion process
1. Editor: milk NT milk fat  milk < containsSubstance > milk fat
Pattern: Substance NT/RT Substance  Substance < containsSubstance > Substance
Therefore milk RT milk protein  milk < containsSubstance > milk protein
Result:

milk < includesSpecific > cow milk milk < includesSpecific > goat milk milk < includesSpecific > buffalo milk milk < containsSubstance > milk fat milk < containsSubstance > milk protein milk < containsSubstance > lactose goat milk < containsSubstance > goat cheese ewe milk < containsSubstance > ewe cheese blood < containsSubstance > blood protein blood < containsSubstance > blood lipids milk NT cow milk milk NT goat milk milk NT buffalo milk milk NT milk fat milk RT milk protein milk RT lactose cows RT cow milk goats RT goat milk ewes RT ewe milk goat milk RT goat cheese ewe milk RT ewe cheese acid soils BT chemical soil types acrisols BT genetic soil types alkaline soils BT chemical soil types aluvial soils BT lithological soil types chemical soil types BT soil types Cichorium BT Asteraceae Cichorium endivia BT Cichorium Cichorium intybus BT Cichorium Cichorium intybus RT coffee substitutes Cichorium intybus RT root vegetables blood NT blood protein blood NT blood lipids Edited relationships Undifferentiated relationships from AGROVOC

1. Editor:
cows RT cow milk  cows < hasComponent > cow milk
Pattern Animal RT BodyPart  Animal < hasComponent > BodyPart
Therefore:
goats NT goat milk  goat < hasComponent > goat milk
Result:

milk < includesSpecific > cow milk milk < includesSpecific > goat milk milk < includesSpecific > buffalo milk milk < containsSubstance > milk fat milk < containsSubstance > milk protein milk < containsSubstance > lactose cows < hasComponent > cow milk goats < hasComponent > goat milk ewes < hasComponent > ewe milk goat milk < containsSubstance > goat cheese ewe milk < containsSubstance > ewe cheese blood < containsSubstance > blood protein blood < containsSubstance > blood lipids milk NT cow milk milk NT goat milk milk NT buffalo milk milk NT milk fat milk RT milk protein milk RT lactose cow RT cow milk goats RT goat milk ewes RT ewe milk goat milk RT goat cheese ewe milk RT ewe cheese acid soils BT chemical soil types acrisols BT genetic soil types alkaline soils BT chemical soil types aluvial soils BT lithological soil types chemical soil types BT soil types Cichorium BT Asteraceae Cichorium endivia BT Cichorium Cichorium intybus BT Cichorium Cichorium intybus RT coffee substitutes Cichorium intybus RT root vegetables blood NT blood protein blood NT blood lipids Edited relationships Undifferentiated relationships from AGROVOC

1. Editor:
acid soils BT chemical soil types  acid soils < isa > chemical soil types
Pattern: X BT * type*  X < isa > * type*
Therefore:
acrisols BT genetic soil types  acrisols < isa > genetic soil types
Result:

milk < includesSpecific > cow milk milk < includesSpecific > goat milk milk < includesSpecific > buffalo milk milk < containsSubstance > milk fat milk < containsSubstance > milk protein milk < containsSubstance > lactose cows < hasComponent > cow milk goats < hasComponent > goat milk ewes < hasComponent > ewe milk goat milk < containsSubstance > goat cheese ewe milk < containsSubstance > ewe cheese acid soils < isa > chemical soil types acrisols < isa > genetic soil types alkaline soils < isa > chemical soil types aluvial soils < isa > lithological soil types chemical soil type < isa > soil types blood < containsSubstance > blood protein blood < containsSubstance > blood lipids milk NT cow milk milk NT goat milk milk NT buffalo milk milk NT milk fat milk RT milk protein milk RT lactose cow RT cow milk goats RT goat milk ewes RT ewe milk goat milk RT goat cheese ewe milk RT ewe cheese acid soils BT chemical soil types acrisols BT genetic soil types alkaline soils BT chemical soil types aluvial soils BT lithological soil types chemical soil types BT soil types Cichorium BT Asteraceae Cichorium endivia BT Cichorium Cichorium intybus BT Cichorium Cichorium intybus RT coffee substitutes Cichorium intybus RT root vegetables blood NT blood protein blood NT blood lipids Edited relationships Undifferentiated relationships from AGROVOC

1. Editor: Cichorium BT Asteraceae  Cichorium < isa > Asteraceae
Pattern: Taxon BT Taxon  Taxon < isa> Taxon
Therefore:
Cichorium endivia BT Cichorium  Cichorium endivia < isa > Cichorium
Result:

milk < includesSpecific > cow milk milk < includesSpecific > goat milk milk < includesSpecific > buffalo milk milk < containsSubstance > milk fat milk < containsSubstance > milk protein milk < containsSubstance > lactose cows < hasComponent > cow milk goats < hasComponent > goat milk ewes < hasComponent > ewe milk goat milk < containsSubstance > goat cheese ewe milk < containsSubstance > ewe cheese acid soils < isa > chemical soil types acrisols < isa > genetic soil types alkaline soils < isa > chemical soil types aluvial soils < isa > lithological soil types chemical soil type < isa > soil types Cichorium < isa > Asteraceae Cichorium endivia <isa> Cichorium Cichorium intybus < isa > Cichorium blood < containsSubstance > blood protein blood < containsSubstance > blood lipids milk NT cow milk milk NT goat milk milk NT buffalo milk milk NT milk fat milk RT milk protein milk RT lactose cow RT cow milk goats RT goat milk ewes RT ewe milk goat milk RT goat cheese ewe milk RT ewe cheese acid soils BT chemical soil types acrisols BT genetic soil types alkaline soils BT chemical soil types aluvial soils BT lithological soil types chemical soil types BT soil types Cichorium BT Asteraceae Cichorium endivia BT Cichorium Cichorium intybus BT Cichorium Cichorium intybus RT coffee substitutes Cichorium intybus RT root vegetables blood NT blood protein blood NT blood lipids Edited relationships Undifferentiated relationships from AGROVOC

1. Editor: Cichorium intybus RT coffee substitutes  Cichorium intybus < usedToMake > coffee substitutes
Pattern: Taxon RT FoodProduct  Taxon < usedToMake > FoodProduct
Therefore: Cichorium intybus RT root vegetables
 Cichorium intybus < usedToMake > root vegetables
Result:

milk < includesSpecific > cow milk milk < includesSpecific > goat milk milk < includesSpecific > buffalo milk milk < containsSubstance > milk fat milk < containsSubstance > milk protein milk < containsSubstance > lactose cows < hasComponent > cow milk goats < hasComponent > goat milk ewes < hasComponent > ewe milk goat milk < containsSubstance > goat cheese ewe milk < containsSubstance > ewe cheese acid soils < isa > chemical soil types acrisols < isa > genetic soil types alkaline soils < isa > chemical soil types aluvial soils < isa > lithological soil types chemical soil type < isa > soil types Cichorium < isa > Asteraceae Cichorium endivia <isa> Cichorium Cichorium intybus < isa > Cichorium Cichorium intybus < usedToMake > coffee substitutes Cichorium intybus < usedToMake > root vegetables blood < containsSubstance > blood protein blood < containsSubstance > blood lipids milk NT cow milk milk NT goat milk milk NT buffalo milk milk NT milk fat milk RT milk protein milk RT lactose cow RT cow milk goats RT goat milk ewes RT ewe milk goat milk RT goat cheese ewe milk RT ewe cheese acid soils BT chemical soil types acrisols BT genetic soil types alkaline soils BT chemical soil types aluvial soils BT lithological soil types chemical soil types BT soil types Cichorium BT Asteraceae Cichorium endivia BT Cichorium Cichorium intybus BT Cichorium Cichorium intybus RT coffee substitutes Cichorium intybus RT root vegetables blood NT blood protein blood NT blood lipids Edited relationships Undifferentiated relationships from AGROVOC

The rules as you go approach Discussion
Main idea: Formulate constraints to assist the editor
Ontology may have many relationship types, perhaps > 100
Constraints limit the relationship types that are possible in a specific case; show the editor only these
If the constraints limit possible relationship types to 1, conversion is automatic
Constraints may depend on Thesaurus to be converted

Constraints Possible ontology relationships Thesaurus Relationships + entity types or values milk < includesSpecific > * milk Substance < containsSubstance > Substance X < isa > * type* Taxon < isa> Taxon GeogrEntity < spatiallyIncludedIn > GeogrEntity BodyPart <isComponentOf> BodyPart ChemSubstance < isa> ChemSubstance milk NT * milk Substance NT Substance X BT * type* Taxon BT Taxon GeogrEntity BT GeogrEntity BodyPart BT BodyPart ChemSubstance BT ChemSubstance

Constraints Possible ontology relationships Thesaurus Relationships + entity types or values Substance < containsSubstance > Substance Substance < containedInSubstance > Substance Substance < usedToMake > Substance Substance < madeFrom > Substance LivingOrganism < hasComponent > BodyPart Taxon < usedToMake > FoodProduct GeogrEntity < isMemberOf > GeogrGrouping Process <performedByInstrument> Object Process <affects> Object ChemSubstance < usedFor > Function Substance RT Substance LivingOrganism RT BodyPart Taxon RT FoodProduct GeogrEntity RT GeogrGrouping Process RT Object ChemSubstance RT Function

Checking by editor
Relationship instances created by editor by selecting from a constraint-generated menu are final
Relationship instances created automatically must be presented to the editor
If the editor determines that the relationship instances are almost always correct, she checks a box accept without checking

Overall conversion process
One master editor must go through the file from start to finish, processing the relationship instances and creating patterns, creating new relationship types as needed
Assistant editors can apply the patterns.
In the first pass, the master editor should deal with the easy cases.
Deal with the remaining cases later. Groups of similar relationship instances can be seen more easily in a smaller set

Adding new relationship types and new relationship instances
AGROVOC does not contain all relationship types or relationship instances for AI applications
Need to add data. For example
Organism X < hasPest > Organism Y
ChemSubstance X < actsAgainst > Organism Y
Organism X < actsAgainst > Organism Y
Plant X < growsIn > Environment Y
FoodProduct X < suitableFor > Diet Y

Conclusion
The rules-as-you-go approach is a realistic method for developing a rich ontology from an existing thesaurus

Building a rich ontology from AGROVOC

by AIMS (Agricultural Information Management Standards) FAO of the UN

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Building a rich ontology from AGROVOC Presentation Transcript