Slide 1

09-05-2002

The Agricultural Ontology Service(AOS)

Effort for Content Standardization in Agriculture

Frehiwot Fisseha (UNFAO)

Frehiwot.Fisseha@fao.org

Slide 2

09-05-2002

Outline

• FAO’s mandate in agricultural information management

• Problems we want to solve

• The current situation

• Proposed solution

• The Agricultural Ontology Service (AOS)

• AOS prototype (The Fishery Ontology Service)

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09-05-2002

FAO’s mandate

• FAO’s main goal is to reduce the number of hungry people by 50% within the year 2015.

• WAICENT (World Agricultural Information Center) is FAO’s approach to fight hunger with information.

• FAO produces a huge amount of data/information in agriculture and related disciplines.

• It is also within FAO’s mandate to make available agriculture related information from other information providers.

• FAO collaborates in information networks which are dedicated to the dissemination of agricultural domain.

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09-05-2002

Problems we want to solve

“The Information Organization” problem faced by Information Managers

At present most information management tasks are performed manually.

... consider the cataloging and indexing task….

Manual cataloging and indexing are labor-intensive processes, requiring special training.

Tools for automating or semi-automating these processes are much in demand.

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09-05-2002

Problems we want to solve

Both parameters are ranking low today!

Recall: Number of Relevant Documents in the Collection

Number of Relevant Documents Identified

Precision: Number of Relevant Documents Identified

Total Number of Documents Identified

“The Information Retrieval” problem faced by Information Users

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09-05-2002

Problems we want to solve

• Topic Trees from categorization schemes and thesauri are rigid and not very expressive

• Machine produced clusters are “flexible”, but imprecise and at times out of context

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09-05-2002

Knowledge Organizations Systems: Metadata Schema

• The subject categorization schemes are not adequately developed to be of use for semantic description for web resources

• The metadata schemas are closely attached to traditional description of bibliographical records

• The Dublin Core Metadata Initiative (DCMI) is a step forward to define core metadata to describe information objects

• Effort is underway to develop Agricultural metadata standards

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09-05-2002

Knowledge Organization Systems: Vocabularies

AGROVOC

NAL Thesaurus

CABI Thesaurus

Dedicated KOSs

Non-dedicated KOSs

e.g., ASFA thesaurus

e.g., the Multilingual Forestry Thesaurus

e.g., the Sustainable Development

website classification

e.g., biological taxonomies such as NCBI and ITIS

GEMET

Other thematic thesauri

Existing Thesauri and Knowledge Organization Systems (KOSs)

Common concepts are not declared

No or very limited interoperability

Insufficient subject + language coverage

Severe maintenance problems

Very limited machine readability

Only very simple encoding of semantic relations

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09-05-2002

Some observations

• No cross navigation between applications

• Full text search engines based on statistical text analysis are imprecise

Systems based only on “machine intelligence” do not show too promising results

• Web crawlers and harvesters do good jobs only on already structured information sources.

Recognition of meaning (semantic analysis) by machines is only possible by using using structured meta-information and formal knowledge description Agreed metadata schemas Controlled vocabularies, Taxonomies

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09-05-2002

The solution we propose- Domain Ontology

An ontology is a formal knowledge organization system

A formal description of the application knowledge

It contains concepts and their definitions

Relations between concepts

Possibility for machine processing

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09-05-2002

What benefits do we expect from Ontology?

– Semantic Organization of websites Knowledge maps Guided discovery of knowledge Easy retrievability of information without using complicated Boolean logic

– Text processing by machines Text Mining on the Web (meaning-oriented access) Automatic indexing and text annotation tools Full text search engines that create meaningful classification (FAO-

Schwartz not related to FAO) (semantic clustering)

– Intelligent search of the Web Building dynamical catalogues from machine readable meta data Cross Domain Search

– Natural Language processing Better machine translation Queries using natural language

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09-05-2002

Guided Browse and Search Facilities

Records found: 5

1. xxxxxxxxxxx

2. xxxxxxxxxxx

3. xxxxxxxxxxx

4. xxxxxxxxxxx

5. xxxxxxxxxxx

BiotopesCropping systems using forestsEconomics of forest productionForestry equipmentSoil science

You may also be interested in...

What would you like to view?

Forest rights issuesParasites of forestsPesticides used in forestsTypes of forest productsUses of forest products

Geographic area

You can further limit by:

x

Africa

Web pageType of resource

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09-05-2002

Context Sensitive Knowledge Access

Conservation agriculture

Farmers like it because it gives them a means of conserving, improving and making more efficient use of their natural resources

About camels and llamas

Descendants of the same rabbit-sized mammal, they have become two of humanity's most versatile domestic animals

Agribusiness and small farmers

Well managed contract farming contributes to both increased income for producers and higher profits for investors

Toward biosecurity

Biological and environmental risks associated with food and agriculture have intensified with economic globalization

Urban food marketing

In the “century of cities”, a major challenge will be providing adequate quantities of nutritional and affordable food for urban inhabitants

Crop science and ethics

In order to continue their contribution to human development, crop scientists must regain credibility

Use your right mouse button to learn more about an italicized word on the page.

Biosecurity:management of all biological and environmental risks associated with food and agriculture, including forestry and fisheries

See also:BiosafetyFood SafetyRisk Management

Or are you interested in...:Food SecurityBiological Diversity

Agricultural Web Page

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09-05-2002

The Collaborative Approach We Want to Adopt

• Only agreed semantic standards guarantee knowledge discovery between different applications.

• Developing Knowledge Organization Systems is resource intensive and requires stakeholder’s agreement and participation.

• Hence, FAO started initiatives to bring interested partners together The AGStandards initiative was launched in October, 2000 to agree on

agricultural metadata standards The Agricultural Ontology Service (AOS) concept paper was publicized in

July 2001.

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09-05-2002

What does Agricultural Ontology Service mean?

The Agricultural Ontology Service is an approach to organize knowledge organization systems that is

International The Internet must become multilingual

MultidisciplinaryThe field of agriculture is broad and multidisciplinary.

CooperativeStakeholders can contribute different expert knowledge

Distributed No central ownership

CoordinatedCoordination must ensure reusability and standardization

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09-05-2002

AOS: Iterative Knowledge Registration

KOS uses components to build

an application

Discussions and choices for amendments to

components

Components: terms, definitions,

relationshipsUsers search and browse

application using components

User feedback

Agricultural Ontology Service (AOS)

Federated storage and description facility

Components: terms, definitions,

relationships

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09-05-2002

Activities to date

• The first AOS workshop took place in Rome, November 2001– A launch group was established with participation of

– Content providers (FAO, CABI)

– Solution providers in the Agricultural Area (ATO -Wageningen, University of Florida)

– Ontology development Groups (AIFB Karlsruhe, CNR Italy) – Ontology experts

The second AOS workshop (January 2002 in Oxford)

– Decision to develop prototypes as proof of concept. – The Fishery Ontology Service (FOS) is one of the prototypes

The third AOS workshop took (May 2002 Florida)– Decision to setup the AOS consortium

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09-05-2002

AOS – a “business model”

• A consortium of Information Providers

• A clearinghouse for semantic standards in agriculture and related discipline.

• One stop access to agreed standards (Ontologies, Metadata schemas, Vocabularies…).

• Participation as a consortium in semantic web activities (Ontoweb).

• Organization of seminars and workshops to further develop and

promote the use of semantic standards.

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09-05-2002

AOS Prototype-

The Fishery Ontology Service (FOS)

Goal: to integrate the multilingual fishery and aquatic resources terminology

– the oneFish Community Directory, – ASFA,– FIGIS, – AGROVOC

Objective:– to have a better tool for document indexing and information retrieval, – to promote interaction and knowledge sharing within the fishery

community