Application of web ontology to harvest estimation of rice in Thailand

Application of web ontology Application of web ontology to harvest estimation of rice to harvest estimation of rice

in Thailandin Thailand

Takuji Kiura*Takuji Kiura*Hitoshi. Toritani**Hitoshi. Toritani**Daisuke Horyu*Daisuke Horyu*

Atsushi Yamakawa*Atsushi Yamakawa*Seishi Ninomiya*Seishi Ninomiya*

*National Agriculture Research Center*National Agriculture Research Center**National Institute for Agro-Environmental Sc**National Institute for Agro-Environmental Sc

ienceience(Japan)(Japan)

BackgroundsBackgrounds

Field Server II (NARC)Field Server II (NARC)Web based Wi-Fi network sensor nodeWeb based Wi-Fi network sensor node

• CaseCase　　 Acryl resinAcryl resin

• CoreCore　　 Field Server-Engine or Field Server-Engine or PICNICPICNIC

• SensorsSensors　　 Temperature, Humidity, Temperature, Humidity, PPFDPPFD Soil moisture, Leaf-Soil moisture, Leaf-wetnesswetness UV, IR UV, IR CO CO22 Camera, Camera, MicroscopeMicroscope

• Data-collection and AIData-collection and AI　　 Fieldserver-AgentFieldserver-Agent

• NetworkingNetworking　　 Wi-Fi AP, Fieldserver-Wi-Fi AP, Fieldserver-GatewayGateway

• GRIDGRID　　 MetBrokerMetBroker

Problems of Field Server Problems of Field Server DataData

• Different Type of Sensors, Time Different Type of Sensors, Time ResolutionResolution– Described in XML files (w/o Described in XML files (w/o

standard)standard)• Semantic ProblemsSemantic Problems

– Sensors are added or removedSensors are added or removed– Time resolution may be changed.Time resolution may be changed.

• Small data size (1KB~10MB) for Small data size (1KB~10MB) for each.each.

Problems of old MetBrokerProblems of old MetBroker

• Adding new databasesAdding new databases– writing new DB wrapperswriting new DB wrappers– Restarting MetBrokerRestarting MetBroker

• Adding new observation ItemsAdding new observation Items– Data Modeling for each itemData Modeling for each item– Writing new data object for each itemWriting new data object for each item

New MetBrokerNew MetBroker

BrokerBroker

Decision-Making Support ServicesDecision-Making Support Services Operational ProductsOperational Products Simulation ModelsSimulation Models Detailed Digital ForecastDetailed Digital Forecast

Inference Engine

DB WrapperDB Wrapper

Basic VocabularyItem Definition

OWL

Station metadata RDBMS

Metadata database

Meteorological databases



2. Request

3. Request

metadata

4. Request data

1. Register

New MetBrokerNew MetBroker

• Adding new databasesAdding new databases– writing Item Definition & Station writing Item Definition & Station

MetadataMetadata

• Adding new observation ItemsAdding new observation Items– Adding new items to basic vocabralyAdding new items to basic vocabraly

•New MetBrokerNew MetBroker can integrate Field can integrate Field Server data with other weather Server data with other weather database.database.

•New MetBrokerNew MetBroker can integrate other can integrate other point observation data (Ex. data from point observation data (Ex. data from other passive sensor networks).other passive sensor networks).

• I18n of client is easier.I18n of client is easier.

• Possibility for personalization.Possibility for personalization.

Advantages of New Advantages of New MetBrokerMetBroker

Develop data integration Develop data integration environment for small and environment for small and distributed agricultural distributed agricultural databasesdatabasesIs OWL/RDF is useful Is OWL/RDF is useful • In other problem domains?In other problem domains?

– Remote Sensing data, Maps, DEMs, etc.Remote Sensing data, Maps, DEMs, etc.

• To integrate different kinds of data?To integrate different kinds of data?– Can we find key property or not?Can we find key property or not?

•Ex. Location is key property to integrate crop experiEx. Location is key property to integrate crop experimental data and Meteorological datamental data and Meteorological data

•1:1 corresponding is not expected 1:1 corresponding is not expected

Use CaseUse Case

Use caseUse case

• harvest estimation of rice in Thailandharvest estimation of rice in Thailand– What kinds of data are required?What kinds of data are required?– From where we can get data?From where we can get data?– How to get them?How to get them?

What kinds of data are What kinds of data are required?required?

• Satellite Sensing DataSatellite Sensing Data

• Digital Elevation ModelsDigital Elevation Models

• Thematic mapsThematic maps– Land usage, Land cover, Irrigated FieldLand usage, Land cover, Irrigated Field

• Field Survey DataField Survey Data

• Ground TruthGround Truth

• Meteorological DataMeteorological Data

• Rice ModelsRice Models

North-East Thailand

World cloud free imageNASA Visible Earth(2001)(MODIS satellite image)

Total land: 169×103 km2 in NET(513×103 km2) in Whole Kingdom

Global Digital Elevation Model(GTPO30)USGS EROS data (1996)

Farm holding land : 91.9×103 km2

(208.6×103 km2)Number of household: 2,621×103

Paddy land: 60.7×103 km2

Forest land: 25.3×103 km2

(Agricultural Statistics of Thailand, 2001)

North-East Thailand

Field Survey data, Ground TruthField Survey data, Ground Truth

Paddock with enough water:transplanting

Neighboring paddock: direct seeding

another paddock in the same field: abandoned

In Khon Kaen, wet season of 2005

From Where we can get From Where we can get data?data?• Satellite Sensing Data, DEM, Thematic mapsSatellite Sensing Data, DEM, Thematic maps

– NASA, NOAA, JAXA, MAFFIN, etc.NASA, NOAA, JAXA, MAFFIN, etc.– Commercial Data ProvidersCommercial Data Providers

• Field Survey DataField Survey Data– Field Survey by our selvesField Survey by our selves– LiteratureLiterature

• Ground TruthGround Truth– Data archive of Sensor NetworkData archive of Sensor Network– Field SurveyField Survey

• Meteorological DataMeteorological Data– Data archive of Sensor Network, Meteorological databases (MetBroker)Data archive of Sensor Network, Meteorological databases (MetBroker)

• Rice ModelsRice Models– ??

How to get data?How to get data?

• Satellite Sensing Data, DEM, Thematic mapsSatellite Sensing Data, DEM, Thematic maps– Web Interface (HTTP POST)Web Interface (HTTP POST)

• Field Survey DataField Survey Data– Field Survey by our selves (XQuery)Field Survey by our selves (XQuery)– Literature (XQuery)Literature (XQuery)

• Ground TruthGround Truth– Data archive of Sensor Network (HTTP GET)Data archive of Sensor Network (HTTP GET)– Field Survey (XQuery)Field Survey (XQuery)

• Meteorological DataMeteorological Data– Data archive of Sensor Network, Meteorological databases (MetBroker)Data archive of Sensor Network, Meteorological databases (MetBroker)

• Rice ModelsRice Models– ??

How to get?How to get?

Name of Dataset

Name of Satellite

Name of Sensor

We need relation between satellite image sensing ontology

and agricultural ontology

Data Integration in Agriculture

WeatherData

Ground Truth

Crop Calendar

When they cultivate rice in Thailand?

Actual Status?

How about weather during rice grow

Ontology RegistryOntology Registry


• Database of Domain Specific OntologyDatabase of Domain Specific Ontology– Resist, Update, Retrieve, Resist, Update, Retrieve, Version ControlVersion Control

• Multi-Ontology Service Multi-Ontology Service – Integrated Ontology?Integrated Ontology?

Ontology Registry 1

2Find Suitable Ontology検索

Add, Delete, Modify

3

New Ontology

I need ontology to solve my

problem…


• Database of Domain Specific OntologyDatabase of Domain Specific Ontology– Resist, Update, Retrieve, Resist, Update, Retrieve, Version ControlVersion Control

• Multi-Ontology Service Multi-Ontology Service – Integrated OntologyIntegrated Ontology

Ontology Registry 1

2Find Suitable Ontology検索

Add, Delete, Modify

3

New Ontology

I need ontology to solve my

problem…

Ontology Registry

Application

1. Developing

Register Ontology

Application

OWLRDF

OWLRDF

(local)

ResourceEditor

2. Localization

(part)

XMLData

(local)

3. Local Utilizes

Local Application A

Local Application B

Local Application C

Local Application D

4. Data Integration

Ontology Metadata

XMLData(A)

XMLData(B)

RelatedDB

Field Survey Data Field Survey Data IntegrationIntegration

No Result!!No Result!!

• Still Under DevelopmentStill Under Development

This research is a part ofGlobal Environmental Data

Integration Project

Abnormal Weather / Climate Change / Wind & Flood Damage / Food &Water Crisis → Poverty，Health，Safety

Understanding and Prediction of Earth system Understanding and Prediction of Earth system

Observation data is insufficientStandardization/quality/archive/

Metadata/format/open to the public/real time

Data integration is insufficientVarious kinds/

non-homogeneity/huge volume/time gap

Data sharing is insufficientTranslation Data to information

Information network

？

？






Information network






Information network

？

？

？

？Create new Knowledge for Earth System Science

For Social Needs

Create new Knowledge for Earth System Science

For Social Needs

Numerical prediction

Flood prediction

Cooperationwith international

Organizations


Organizations

Metrologicalinformation

Better use of data

Agriculturemanagement

Disperseduse

Predictionneeds

IntegratedInformation

Numerical prediction

Flood prediction


Organizations


Organizations

Metrologicalinformation

Better use of data

Agriculturemanagement

Disperseduse

Predictionneeds


data


Oceanic data

Flood data

Earth observation dataCollection/quality management

Cooperation with International Research Center

Satellite data

Ground observation data

Cooperation with Earth ObservationPlans

Integration method

data


Oceanic data

Flood data

Earth observation dataCollection/quality management

Cooperation with International Research Center

Satellite data

Ground observation data

Cooperation with Earth ObservationPlans

Integration method

Centralized Data Integration & Fusion①data archive, storage, integration②data assimilation, visualization, mining③design for database schema④data collection and distribution⑤sensor data fusion

Integration of Distributive Data

①constriction of ontology registry

②service by ontology registry③distinguished DB for agriculture④distinguished DB for satellite data

Core System









Core System

Thank you for your Thank you for your attentionattention

New MetBroker DemoNew MetBroker Demohttp://www.agmodel.org/metbroker/demo.html

Application of web ontology to harvest estimation of rice in Thailand

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