DEVELOPING
SEMANTICALLY RICH APPLICATIONS
PEDRO LOPES [email protected] GAM6 - Montpellier
September 27th, 2010
1
‣ CLIENT SIDE
• User Interfaces
‣ Semantically rich applications
‣ Meaningful results
‣ Context
‣ Enrich text
• Information Visualization
• Augmented browsing
‣ SERVER SIDE
• Ontology
• Semantically rich resources
• Meaningful relationships
• Reasoning
• Context-aware
• Artificial Intelligence
• Linked Data
• Intelligent resource networks
SEMANTIC WEB RICHNESS
2
‣ CLIENT SIDE
• User Interfaces
‣ Semantically rich applications
‣ Meaningful results
‣ Context
‣ Enrich text
• Information Visualization
• Augmented browsing
‣ SERVER SIDE
• Ontology
• Semantically rich resources
• Meaningful relationships
• Reasoning
• Context-aware
• Artificial Intelligence
• Linked Data
• Intelligent resource networks
SEMANTIC WEB RICHNESS
From server side semantic richness to client side interfaces ?
2
Cardiac
...
ECG
CLIENT SIDE
3
Cardiac
...
ECG
CLIENT SIDE
3
Cardiac
...
ECG
CLIENT SIDE
3
Cardiac
...
ECG
CLIENT SIDE
3
Cardiac
...
ECG
CLIENT SIDE
From simple result listingsto semantically rich interfaces !
3
SERVER SIDE
RDF
OWL SPARQL
Linked Data
Ontology
Endpoint
Mapping
Triplestore
Federation
Text
Query
XML
DBPedia
FOAF
Bio2RDF
D2R
Tim Berners-Lee
Integration
Composition
SADI
Knowledge
Identity
Mashup
Network4
SERVER SIDE
RDF
OWL SPARQL
Linked Data
Ontology
Endpoint
Mapping
Triplestore
Federation
Text
Query
XML
DBPedia
FOAF
Bio2RDF
D2R
Tim Berners-Lee
Integration
Composition
SADI
Knowledge
Identity
Mashup
Network4
‣ ONE QUERY, MULTIPLE INSTANCES
• Connect distinct resources
‣ Cross information
‣ Merge datasets
‣ CHALLENGES
• How to query so many distinct resources?
• How to map results?
‣ SOLUTIONS
• SPARQL querying
‣ SQL for the Semantic Web
• Ontology mapping
‣ Modeling for the Semantic Web
1
2
3
...
n
FEDERATED QUERYING
5
‣MULTIPLE LSDBs
• Get data from distinct LOVD instances
FEDERATED QUERYING IN GEN2PHEN
CHINA
AUSTRALIA
FRANCE
...
UK
6
‣MULTIPLE LSDBs
• Get data from distinct LOVD instances
FEDERATED QUERYING IN GEN2PHEN
CHINA
AUSTRALIA
FRANCE
...
UK
‣MULTIPLE MOLGENIS
• Connect data models distributed in multiple MOLGENIS instances
PHENO
VARIO
PAGE
...
HGVbaseG2P
6
‣MULTIPLE LSDBs
• Get data from distinct LOVD instances
FEDERATED QUERYING IN GEN2PHEN
CHINA
AUSTRALIA
FRANCE
...
UK
‣MULTIPLE MOLGENIS
• Connect data models distributed in multiple MOLGENIS instances
PHENO
VARIO
PAGE
...
HGVbaseG2P
6
‣ DATA ACCESS
• Direct
‣ No need for wrappers or mediators
‣ No need for data mappings or transformations
• Homogeneous
‣ Results are retrieved as XML/JSON
• Coherent
• Easy to parse/browse
• Client-side ready
ADVANTAGES
‣ DATA MODELS
• Semantic, not relational
‣ Ontology
‣ No need for direct connections
• INNER JOIN
• Reasoning
‣ Ask questions
‣ Process answers
7
SEMANTICALLY RICH INTERFACE
DEMO
FEDERATED QUERIES
8
THANK YOU!
QUESTIONS?
9
Recommended
