accessing meteorological data using ontology

National Agriculture and Food Research Organization National Agricultural Research Center

Data Mining and GRID Research Team Takuji Kiura, Atsushi Yamakawa, Xinwen Yu, & Seishi Ninomiya

Accessing Meteorological DataUsing Ontology

Takuji KiuraAtsushi Yamakawa

Xin Wen YuSeishi Ninomiya

NARC, NARO, Japan



MetBroker

WebService for accessing Meteorological Data

20000 Observation Point

気象 DB

気象 DB

気象 DB

アプリケーション



MetBroker

気象 DB

気象 DB

気象 DB




MetBroker

気象 DB

気象 DB

気象 DB




MetBroker

W DB

気象 DB

気象 DB




MetBrokerMetBroker

Weather DB

Weather DB

Client APP

Client APP

Client APP

Weather DB



Agricultural applications and databases

Agricultural applications need several different types of data setDatabases needed for the applications are usually maintained and managed by different organizations and are located in different placesThose databases are heterogeneous in access method, data formats, available items, time resolution etc.



Example of Heterogeneity of Metrological Database

ItemAir Temperature, Wind, Rain, Radiation, etc.

Sub ItemRain Amount, Rain Intensity, Rainy Days, etc.

Time ResolutionSub Hourly, Hourly, Daily, Monthly, etc.

SummarizationMean, Maximum, Minimum, Total, etc.

Equipment



Fie ld Server II (NARC )

• C aseA cry l res in

• C o reF ield S erver-E ngine o r P IC N IC

• S en so rsT em peratu re, H um id ity , P P F DS oil m ois tu re, L eaf-w etnessU V , IRC O 2C am era, M icroscope

• D ata-co llec tio n an d A IF ieldserver-A gen t

• N etw o rk ingW i-F i A P , F ieldserver-G atew ay

• G R IDM etB roker



F ie ld S erver D ata

• D if feren t T y p e o f S en s o rs , T im e R es o lu tio n

– D escribed in X M L files (w /o s tandard)• S e m a ntic P rob le m s

– S ensors are added o r rem oved

– T im e reso lu tion m ay be changed .

• S m all d a ta s ize (1 K B ~ 1 0 M B ) fo r each .



Solution by Ontology

BrokerBroker

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

Inference Engine

DB WrapperDB Wrapper

Item Definition OWL

Station metadata RDF

Metadata database

Meteorological databases



2. Request

3. Request

metadata

4. Request data

1. Register



Sample Basic Vocabulary<owl:Class rdf:ID="DailyMaxAirTemperature"> <rdfs:subClassOf rdf:resource="#MaxAirTemperature"/> <rdfs:subClassOf> <owl:Restriction> <owl:allValuesFrom> <owl:Class rdf:about="#DailyMaximum"/> </owl:allValuesFrom> <owl:onProperty> <owl:ObjectProperty rdf:about="#summaryKind"/> </owl:onProperty> </owl:Restriction> </rdfs:subClassOf></owl:Class>

<owl:Class rdf:about="#DailyMaximum"> <rdfs:subClassOf rdf:resource="#Maximum"/> <rdfs:subClassOf> <owl:Restriction> <owl:allValuesFrom rdf:resource="#Daily"/> <owl:onProperty> <owl:ObjectProperty rdf:about="#duration"/> </owl:onProperty> </owl:Restriction> </rdfs:subClassOf></owl:Class> Sample file:

http://www.agmodel.org/MetBroker.owl

“”DailyMaxAirTemperature” is a subclass of “MaxAirTemperature”

“”DailyMaxAirTemperature” is recognized as maximum and daily data



Sample Item Definition

<met:DailyMaxAirTemperature rdf:ID="ame_day.temp_max"><met:summaryKind rdf:resource="http://www.agmodel.org/MetBroker.owl#DailyMaximumOfSampleEvery10Minutes"/></met:DailyMaxAirTemperature>

<met:HourlySampleAirTemperature rdf:ID="ame_time.temperature"><met:summaryKind rdf:resource="http://www.agmodel.org/MetBroker.owl#SampleOnTheHour"/></met:HourlySampleAirTemperature>

A sample file is available on http://www.agmodel.org/Aclima.owl

Local item name

“ame_day.temp_max” is recognized as maximum and daily data based

on every 10 minutes data



Sample Station Metadata <met:MetStation rdf:ID="01">

<rdfs:label xml:lang=“en">

Ag. Res. Inst. Representative Observation Station

</rdfs:label>

<met:alt>64.0</met:alt>

<met:log>139.2874298095703</met:log>

<met:lat>35.34185791015625</met:lat>

<met:belongTo>http://www.agmodel.org/Kanagawa.rdf</met:belongTo>

<met:metCatalog>

<met:MetCatalog>

<met:metElement>&kngw;#DailyAverageWindVelocity</met:metElement>

<met:catalogStart>1995-12-31T15:00:00+0000</met:catalogStart>

<met:measurementHeight>2.0</met:measurementHeight>

<met:MetCatalog>

</met:metCatalog>

…….

</met:MetStation>

Description of weather station

The details of measured items

This item is defined in Item definition file



DEMO (Single station access)

DBBroker

Inference Engine

1. ReuqestResolution DailySummary MeanItem Air Temperature

Basic Vocabulary<owl:Class rdf:ID="DailyMeanAirTemperature“/>

Database : Item definition<met: DailyMeanAirTemperature rdf:ID=“Air“ />

2. Find the basic vocabulary that is equivalent to the request

3. Find the local item that is equivalent to “DailyMeanAirTemperature”

4. Pass the local item “Air”

5. Query the database using the

local item “Air”



DEMO

Basic Vocabulary Tree

Data Access using Google Maps

http://www.agmodel.org/metbroker/demo.html



Summary

We show you a demo application of New MetBroker that uses small single ontology to integrate distributed Meteorological Data virtually.

Using “Temperature” you can get mean, maximum, and minimum air temperature and soil temperature

Japanese item names and English item names are supported

May support other languages without any change in program sources.

accessing meteorological data using ontology

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