Developing Semantically Rich Applications

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Semantic Web short talk. Introducing client-side semantic web and federated querying at GEN2PHEN GAM6

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  • DEVELOPING

    SEMANTICALLY RICH APPLICATIONS

    PEDRO LOPES pedrolopes@ua.ptGEN2PHEN 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