Developing Semantically Rich Applications

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DEVELOPING

SEMANTICALLY RICH APPLICATIONS

PEDRO LOPES pedrolopes@ua.pt GEN2PHEN GAM6 - Montpellier September 27th, 2010

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SEMANTIC WEB RICHNESS ‣ CLIENT SIDE • User Interfaces

‣ SERVER SIDE • Ontology

‣ Semantically rich applications

• Semantically rich resources

‣ Meaningful results

• Meaningful relationships

‣ Context ‣ Enrich text • Information Visualization

• Augmented browsing

• Reasoning • Context-aware • Artificial Intelligence • Linked Data • Intelligent resource networks

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SEMANTIC WEB RICHNESS ‣ CLIENT SIDE • User Interfaces

‣ SERVER SIDE • Ontology

‣ Semantically rich applications

• Semantically rich resources

‣ Meaningful results

• Meaningful relationships

‣ Context

• Reasoning

‣ Enrich text

• Context-aware • Artificial Intelligence

• Information Visualization

• Augmented browsing

• Linked Data • Intelligent resource networks

From server side semantic richness to client side interfaces

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CLIENT SIDE Cardiac ... ECG

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CLIENT SIDE Cardiac ... ECG

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CLIENT SIDE Cardiac ... ECG

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CLIENT SIDE Cardiac ... ECG

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CLIENT SIDE Cardiac ... ECG

From simple result listings to semantically rich interfaces

!

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SERVER SIDE

Composition Tim Berners-Lee DBPedia

RDF OWL

Federation Endpoint

SPARQL

Query

Knowledge

FOAF

SADI

Integration Identity Triplestore Ontology

Mashup

Linked Data

Mapping XML

D2R Text

Network

Bio2RDF 4


SERVER SIDE

Composition Tim Berners-Lee DBPedia

RDF OWL

Federation Endpoint

SPARQL

Query

Knowledge

FOAF

SADI

Integration Identity Triplestore Ontology

Mashup

Linked Data

Mapping XML

D2R Text

Network

Bio2RDF 4


FEDERATED QUERYING ‣ ONE QUERY, MULTIPLE INSTANCES • Connect distinct resources ‣ Cross information

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‣ Merge datasets

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‣ CHALLENGES • How to query so many distinct resources?

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• How to map results?

‣ SOLUTIONS • SPARQL querying

...

‣ SQL for the Semantic Web • Ontology mapping

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‣ Modeling for the Semantic Web

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FEDERATED QUERYING IN GEN2PHEN ‣ MULTIPLE LSDBs • Get data from distinct LOVD instances

CHINA

AUSTRALIA

FRANCE

... UK

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FEDERATED QUERYING IN GEN2PHEN ‣ MULTIPLE LSDBs

‣ MULTIPLE MOLGENIS

• Get data from distinct LOVD instances

CHINA

• Connect data models distributed in multiple MOLGENIS instances

PHENO

AUSTRALIA

VARIO

FRANCE

PAGE

... UK

...

HGVbaseG2P

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FEDERATED QUERYING IN GEN2PHEN ‣ MULTIPLE LSDBs

‣ MULTIPLE MOLGENIS

• Get data from distinct LOVD instances

CHINA

• Connect data models distributed in multiple MOLGENIS instances

PHENO

AUSTRALIA

VARIO

FRANCE

PAGE

... UK

...

HGVbaseG2P

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ADVANTAGES ‣ DATA ACCESS • Direct ‣ No need for wrappers or mediators ‣ No need for data mappings or transformations • Homogeneous ‣ Results are retrieved as XML/JSON • Coherent

‣ DATA MODELS • Semantic, not relational ‣ Ontology ‣ No need for direct connections • INNER JOIN

• Reasoning ‣ Ask questions ‣ Process answers

• Easy to parse/browse • Client-side ready

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DEMO SEMANTICALLY RICH INTERFACE FEDERATED QUERIES

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QUESTIONS? THANK YOU!

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