how to build ontologies - a case study of agriculture activity ontology

Hideaki TakedaNational Institute of Informatics (NII)

kNeXI 2017 (International Workshop on kNowledge eXplication for Industry)15 November, 2017, Tokyo, Japan

How to build ontologies - a case study of Agriculture Activity Ontology

Today’s Talk

• Overview of Agriculture Activity Ontology (AAO)

• How to build AAO

• Overview of Crop Vocabulary (CVO)

Standardization of Agricultural Activities

Background

Issues

Purpose

Agricultural IT systems are widely adopted to manage and record activitiesin the fields efficiently. Interoperability among these systems is needed tointegrate and analyze such records to improve productivity of agriculture.

To provide the standard vocabulary by defining the ontology for agricultural activity

Data in agricultural IT systems is not easy to federate and integrate due to the variety of the languages

It prevents federation andintegration of these systems andtheir data.

http://www.toukei.maff.go.jp/dijest/kome/kome05/kome05.html

しろかき

“Puddling”

砕土

“Pulverization”

代かき

“Puddling”

代掻き

“Puddling”

代掻き作業

“Puddling Activity”

荒代(かじり)

“Coarse pudding”

荒代かき

“Coarse pudding”

整地

“Land grading”均平化

“land leveling”

Define activity concepts

Define hierarchy

Seeding: activity to sow seeds on fields for seed propagation.

Purpose: seed propagationPlace : fieldTarget : seedAct : sow

“Seeding”

Define activities with properties and their values

The hierarchy of activities is organized by property- New properties and their values are added

- “purpose”, “act”, “target”, “place”, “means” , “equipment”, “season”, and “crop” in order.

- Property values are specialized

Seeding

property value

Agricultural Activity Ontology(AAO)

Formalization by Description Logics

Crop production activity

Crop growth activity

purpose：crop production

purpose：crop growth

Agricultural activity

Activity for control of propagation

Activity for seed propagation

purpose：control of propagation

purpose：seed propagation

Seedingact : sowtarget：seedplace：field

Activity for seed propagation

Seeding

Designing of Agricultural Activity Ontology(AAO)

Differentiate concepts by property

purpose : seed propagationplace : paddy fieldtarget : seedact : sowcrop：rice

purpose : seed propagation purpose : seed propagationplace : fieldtarget : seedact : sow

Agricultural activity >…> Activity for seed propagation > Seeding

purpose : seed propagationplace : well-drained paddy fieldtarget : seedact : sowcrop：rice

Direct sowing of rice on well-drained paddy field Direct seeding in flooded paddy field

Well-drained paddy field < field paddy field < field


Activity for seeding Direct seeding in flooded paddy field

Direct sowing of rice on well-drained paddy field

Seeding on nursery box

The Structuralizaion of the Agricultural Activities (Protégé)


Polysemic concepts

[disjunction form]

[conjunction form]

Pudlling

Subsoil breaking

PulverizationLand preparation

Water retentionActivity for water

management

Land leveling

Polysemicrelationship

Pulverization by harrow

purpose : pulverizationpurpose : water retentionpurpose : land leveling

Definition of agriculture activities with multiple purposes or other properties.

Puddling


Water retention

Land leveling Pulverization

Puddling

Polysemic concepts (Protégé)


Synonym


Expressions in multiple languages are also represented as synonyms. (It is important especially for non-English speaking countries)

Reasoning by Ontology

Reasoning by Agriculture Activity Ontology

Activity for biotic control

Activity for suppression of pest animals

Activity for suppression of pest animals by physical

means

control of pest animals

Physical means

means(0,1)

purpose(0,1)

Biotic control

purpose(0,1)

Activity for suppression of pest animals by chemical

means

Chemical means

purpose(0,1)

means(0,1)

Making scarecrow‘

suppression of pest animals

Purpose(0,1)

build

act(0,1)

scarecrow

target(0,1)

Physical means

Means(0,1)

？ Example of「Making scarecrow」

?


Infer the most feasible upper concept for the given constraints for a new words

Reasoning by Ontology

かかし作り

物理的手段

means(0,1)

means(0,1)

Inference with SWCLOS

[1] Seiji Koide, Theory and Implementation of Object Oriented Semantic Web Language, PhD Thesis, Graduate University for Advance Studies, 2011

[1]

[1]

Activity for biotic control

Activity for suppression of pest animals

Activity for suppression of pest animals by physical

means

control of pest animals

Physical means

means(0,1)

purpose(0,1)

Biotic control

purpose(0,1)


Activity for suppression of pest animals by chemical

means

Chemical means

purpose(0,1)

means(0,1)

Making scarecrow

make

act(0,1)

scarecrow

target(0,1)

Infer the most feasible upper concept for the given constraints for a new words

Reasoning by Agriculture Activity Ontology

Making scarecrow is a subclass of Activity for suppression of pest animals by physical means

Applying Agricultural Activity Ontology

URI

Give a unique URI for each concept

http://cavoc.org/aao/ns/1/は種

http://www.cavoc.org/ http://www.cavoc.org/aao

Web Services based on Agriculture Activity Ontology

• Version Historyver. 141: published on January 5, 2017. 410 words and concepts.

ver 1.33: published on September 23, 2016. 374 words and concepts,

ver 1.31 : published on April 22, 2016. 355 words collected, the concepts were classified with 8 attributes.

ver 1.10 : published on February 12, 2016. 330 words collected, new words are collected.

ver 1.00 : published on November 2, 2015. 301 words collected, defined with Description Logics, introductionof property.

ver 0.94 : published on May 12, 2015. 185 words collected.


Data Sharing

The data of AAO can be downloaded in the RDF/Turtle formats from cavoc.org/aao/.

we provide a SPARQL endpoint for users to explore AAO data using SPARQL queries.

[the SPARQL Endpoint of AAO][Download]


Converting synonyms to core vocabulary

http://www.tanbo-kubota.co.jp/foods/watching/14_2.html

“Puddling Activity”“sowing”

…

AAO

PuddlingSeeding

…

Converting

[system]

API

Puddling Activity and sowing…

[system’]

Puddlingand seeding…

How did we build Agriculture Activity Ontology?

• Share the experience of building ontologies

• Design Process– 0th Step: Project Formation

– 1st Step: Survey

– 2nd Step: Analysis of Data

– 3rd Step: Proposed Structure (1st)

– 4th Step: Introduction of Descriptions Logics

– 5th Step: Evaluation and Enrichment by domain experts

Design Process- 0th Step: Project Formation -

• Cross-ministerial Strategic Innovation Promotion Program (SIP), “Technologies for creating next-generation agriculture, forestry and fisheries” (funding agency: Bio-oriented Technology Research Advancement Institution, NARO).

• Project aim: define common vocabulary on agriculture activity – To share knowledge among farmers of different crops and different

regions and different systems – Human understandable and machine readable

• Four members from two organizations– Ontology Expert Researchers from National Institute of Informatics

(NII)

– Information Expert Researchers from National Agriculture and Food Organization (NARO)

Design Process- 1st Step: Survey -

• Survey of existing vocabularies– Agrovoc: defined by FAO. Most popular and famous

vocabulary in the domain• International• Maintenance• Machine readable (LOD)

– Agropedia• In Japanese• With explanations

– MAFF Guideline (prototype version)• Official• Related to Elements in Official Statistics

AGROVOC

Thesaurus

AGROVOC organizes words by synonym, narrower/broader, and relatedrelationship.

harvesting topping(beets)

baling

gleaning

mechanical harvesting

mowing

AGROVOC. . .

Narrower/broader relationshipis not clearly defined. Sorelationship among botherwords are often mixed andmisunderstood.

relationship between siblings

AGROVOC is the most well-known vocabulary in agriculture supervised by Food and Agriculture Organization(FAO) and the thesaurus containing more than 32,000 terms of agriculture, fisheries, food, environment and other related fields.

The number of activity names about rice farming, which is important in Asia including Japan, are insufficient.

農業ITシステムで用いる農作

業の名称に関する個別ガイドライン（試行版）

Design Process- 2nd Step: Analysis of data

Design Process- 3rd Step: Proposed Structure (1st) -

Define hierarchy clearly

Accept various synonymous words

Hierarchy is convenient for human to understand and for computers toprocess. But it often be confused by mixing different criteria on relationshipamong concepts/words. It causes difficulty when adding new concepts/wordsand when integrating different hierarchies.

Names for a single concept may be multiple by region and by crop

Define relationship clearly between upperand lower concepts as basis of classification

Clarify an entry word and their synonyms for each concept

harvesting topping(beets)

baling

gleaning

mechanical harvesting

mowing

Thesaurus (AGROVOC)

. . .

harvesting mechanical harvesting

manual harvesting

. . .

Inheritrelationship between siblings

Representation: ”Harvesting”

Design Process- 4th Step: Introduction of Description Logics -

• Consideration of the structure

– Discovery of logical structure

– Reformation of the structure by Description Logics• Use of a property for each is-a relation

– Introduction of a new property

– Is-a hierarchy of a property value

• Re-arrangement of classes


manual harvesting

. . .

Harvest Harvest

Harvest

Inherit

byMachine

manually

＋

＋


[Act]

Ontology


manual harvesting

. . .


[Means]

[Means]

Design Process- 5th Step: Evaluation and Enrichment by domain experts -

• Ask evaluations to experts

– individual crops experts

– Farmer management system developer

• Feedback

– Some alternation of class structure

– Many new words• Crop-specific words

• Area-specific words (dialect)

What we’ve learnt

• Survey and critics of existing vocabularies– Understanding of pros and cons– Fix the target

• Data-driven approach– Avoid too abstract discussion

• Small group of knowledgeable persons of two sides (domain and informatics)– Constructive discussion

• Make the core then extend it– Introduction of AI experts– Introduction of more domain experts

• Communication is important

32

CVO : Crop Vocabulary

Standardization of crop name

Image of distribution flow of agriculture product, and information flow

Administrative agencies

Farmers

[ Pea, Pod pea]

[ Pod pea]

Distributor

[ Pod pea

“Kinusaya”]

Retailers

[ Pod pea

“Kinusaya”] Product history

Product review

Cultivation technology Agricultural chemical

use reference

--- [Food chain]----

Information flow Distribution flow

Pod PeaSynonyms；Scientific name; Pisum sativum

Mature/Immature ; Immature

Edible part; Seed, Pod

PeaSynonyms；Garden pea

Scientific name; Pisum sativum

Mature pea seedSynonyms；Pea (mature seed)

Scientific name; Pisum sativum

Mature/Immature ;Mature

Edible part; Seed

・Species is not crop!・A single species is treated in different ways

by different stakeholdersby different market needas different food

【Cultivar list】・・・・

Green peasSynonyms；Scientific name; Pisum sativum

Mature/Immature ; Immature

Edible part; Seed

【Cultivar list】“Usui”・・・・

【Cultivar list】“Kinusaya” ・・・

Standardization of crop name

Crop Vocabulary (CVO)

• Crop Concept– Crop name

• Synonym

– Japanese common name– Scientific name– Edible/non-edible– Edible part– Mature/Immature– Other properties

• Planting method …

id=455045

オクラ= okra

Food names In food composition database by MEXT(Ministry of education, culture, sports, science and technology, JAPAN)

Crop names in Agricultural chemical residue reference by MHLW(Ministry of health, labourand welfare, JAPAN)

Crop names in Agricultural Chemical Use Reference by Ministry of Agriculture, Forestry and Fisheries, JAPAN)

Registered cultivar names

by CAVOC

CVO オクラ(果実)= okra(fruits)

オクラ= okraオクラ

= okra

オクラ= okra

WIKIPEDIA

NCBI Taxonomy DB

CVO (Crop Vocabulary) linked to other vocabularies

CAVOC provides URI for crop names and API

based on CVO

URI of Crop Names(CVO)

Crop name

Species name

English name

Synonym

Scientific name

Broader concept

Link to URI of ..

Agricultural Chemical Use Reference Food names In food composition databaseAgricultural chemical residue reference Registered cultivar namesNCBI taxonomy DatabaseWIKIPEDIA

List of crop names

URI of Crop Names(Crop names in Agricultural Chemical Use Reference )

Link to URI of CVO

List of crop names

Crop name

Class name

Property values

Connection among multiple datasets

API based on CVO

Food names In food composition database has food name, food number, English name and scientific name.

Crop names in Agricultural Chemical Use Reference has crop name, class name and property value.

Food names In food composition database

Crop names in Agricultural Chemical Use Reference

CVO

http://cavoc.org/cvo/api/CVO_TekiyounousakumotuToCVO.php?term=いちょう(種子)

Food name : ぎんなん(イチョウ)Food number : 05008,05009English name : GinkgoScientific name : Ginkgo biloba

Crop name : イチョウ(種子)Class name : 果樹類Property value :種子を収穫するもの

Crop name : ギンナンLink to : イチョウ(種子)ぎんなん(イチョウ)

Input : crop name in Agricultural Chemical Use Reference.Output : English name and Scientific name

How to build CVO

• Survey and interview to stakeholders– JA

– Farmers

– Agricultural chemical experts

– Market operators

– Food distribution companies

• It turned out that the farmers and JA put the most importance on the regulation of use of agricultural chemicals

How to build it - Data-drivenCrop names in Agricultural Chemical Use Reference by MAFF

Guideline name by MAFF(2017) CVO (tentative)

Guideline name by MAFF (2016)

Crop statistics by MAFF

Household budget survey by MIC

Vegetable Code Encourage

varieties by MAFF

Food names In food composition database by MEXT

MAFF (Ministry of Agriculture, Forestry and Fisheries, JAPAN)MEXT(Ministry of education, culture, sports, science and technology, JAPAN)MIC (Ministry of Internal Affairs and Communications)

How to build CVO

• Crop =/= Species• Crop = Species

Species + edible/non-edible+ edible part+ mature/un-mature+ growing method

+ Cultivar• Careful decision by experts about which entity should be

registered in CVO– How really it is used in the society (market, farmers …)– Give the suitable names

• “Species name” (generic)• “species name” (“edible part”)

• Feedback from more experts

Name?

http://cavoc.org/

Common Agricultural VOCabulary

Agriculture Activity Ontology (AAO) ver 1.42

http://cavoc.org/aao/

Conclusion

There are no gold way to build ontologies. We adopt the bottom-up and minimum commitment approach. It requires time and effort. We believe that it is successful at least to build AAO and CVO.

Crop Vocabulary ver 1.02

http://cavoc.org/cvo/

how to build ontologies - a case study of agriculture activity ontology

Internet