SlideShare a Scribd company logo
1 of 18
Download to read offline
ELIS  –  Mul*media  Lab
Reasoned
SPARQL
Sam Coppens, Miel Vander Sande, Ruben Verborgh,
Erik Mannens, Rik Van de Walle,
SPARQL
JACK BAUER INTERROGATION TECHNIQUE
When asking politely just isn’t enough
Reasoning on
distributed data
Reasoned
SPARQL
ELIS  –  Mul*media  Lab
Goal: Reasoning as a Service
Smart SPARQL agents
outsource reasoning to appropriate infrastructure
(client-side, server-side, or third party)
Client
Server /
Data
Provider
Reasoning OWL QLOWL RL / EL
ELIS  –  Mul*media  Lab
Smart SPARQL Agent
Goal: Reasoning as a Service
Client
Server /
Data
Provider
Reasoning
Reasoning
Grid
Goal: Reasoning as a Service
Smart SPARQL agents
outsource reasoning to appropriate infrastructure
(client-side, server-side, or third party)
ELIS  –  Mul*media  Lab
Distributed Reasoning (LarKC)
Identification
Selection
Transformation
Reasoning
Decision
REASON
<http://test.com/rules.n3>
OVER {
?s ?p ?o
}
WHERE {
?s ?p ?o
}
Solution: ‘Reason’ Query Form
ELIS  –  Mul*media  Lab
SPARQL 1.1: Support for entailment regimes
(RDFS, OWL) by means of BGP matching
Data provider decides inference rules support
With reasoned SPARQL, the data consumer
choses the inference rules for reasoning
ELIS  –  Mul*media  Lab
Nested Queries
SELECT ?child
WHERE {
:Jenna :child ?child .
{
REASON {
{ ?x :parent ?y } => { ?y :child ?x } .
}
OVER {
?s :parent ?o .
}
WHERE {
?s a :Person; :parent ?o .
}
}
}
ELIS  –  Mul*media  Lab
•
Workload Balancing
REASON {
{ ?x foaf:knows ?y } => { ?y foaf:knows ?x } .
}
OVER {
:Jenna foaf:knows ?person .
}
WHERE{
{
SERVICE <http://example.org/sparql> {
:Jenna foaf:knows ?person .
} } UNION {
SERVICE <http://example2.org/sparql> {
:Jenna foaf:knows ?person .
} }
}
ELIS  –  Mul*media  Lab
Pitfalls
Incomplete reasoning / errors
like SPARQL
Server-side vs. client-side reasoning
probably OWL QL reasoning
server-side BGP matching
OWL RL and EL will happen client-side
ELIS  –  Mul*media  Lab
Distributed reasoning on top of distributed querying
Reasoning as a service
Use Cases
End user
Distributed
Reasoning
Framework
Endpoints
Endpoints
Endpoints
Client
External
Reasoner
Endpoint
ELIS  –  Mul*media  Lab
Reasoning on
distributed data
SPARQL
Reasoned
SPARQL
ELIS  –  Mul*media  Lab
ELIS  –  Mul*media  Lab
Sam Coppens, Miel Vander Sande, Ruben Verborgh,
Erik Mannens, Rik Van de Walle,
Reasoned
SPARQL
Using SPARQL agents to obtain answers
through distribution and reasoning

More Related Content

What's hot

DBpedia's Triple Pattern Fragments
DBpedia's Triple Pattern FragmentsDBpedia's Triple Pattern Fragments
DBpedia's Triple Pattern FragmentsRuben Verborgh
 
Distributed Affordance
Distributed AffordanceDistributed Affordance
Distributed AffordanceRuben Verborgh
 
The web – A hypermedia story
The web – A hypermedia storyThe web – A hypermedia story
The web – A hypermedia storyRuben Verborgh
 
Querying federations 
of Triple Pattern Fragments
Querying federations 
of Triple Pattern FragmentsQuerying federations 
of Triple Pattern Fragments
Querying federations 
of Triple Pattern FragmentsRuben Verborgh
 
The Lonesome LOD Cloud
The Lonesome LOD CloudThe Lonesome LOD Cloud
The Lonesome LOD CloudRuben Verborgh
 
(Re-)Discovering Lost Web Pages
(Re-)Discovering Lost Web Pages(Re-)Discovering Lost Web Pages
(Re-)Discovering Lost Web PagesMichael Nelson
 
Toronto OpenRefine MeetUp Nov 2015
Toronto OpenRefine MeetUp Nov 2015Toronto OpenRefine MeetUp Nov 2015
Toronto OpenRefine MeetUp Nov 2015Martin Magdinier
 
Getting Started With The Talis Platform
Getting Started With The Talis PlatformGetting Started With The Talis Platform
Getting Started With The Talis PlatformLeigh Dodds
 
SPARQL Query Forms
SPARQL Query FormsSPARQL Query Forms
SPARQL Query FormsLeigh Dodds
 
On the Persistence of Persistent Identifiers of the Scholarly Web
On the Persistence of Persistent Identifiers of the Scholarly WebOn the Persistence of Persistent Identifiers of the Scholarly Web
On the Persistence of Persistent Identifiers of the Scholarly WebMartin Klein
 
Full text search
Full text searchFull text search
Full text searchdeleteman
 
Designing RESTful APIs
Designing RESTful APIsDesigning RESTful APIs
Designing RESTful APIsanandology
 
Demystifying Apache Spark
Demystifying Apache SparkDemystifying Apache Spark
Demystifying Apache SparkAdi Polak
 
A Spark-Based Intelligent Assistant: Making Data Exploration in Natural Langu...
A Spark-Based Intelligent Assistant: Making Data Exploration in Natural Langu...A Spark-Based Intelligent Assistant: Making Data Exploration in Natural Langu...
A Spark-Based Intelligent Assistant: Making Data Exploration in Natural Langu...Databricks
 
Improving data interoperability in Python and R
Improving data interoperability in Python and RImproving data interoperability in Python and R
Improving data interoperability in Python and RWes McKinney
 

What's hot (20)

DBpedia's Triple Pattern Fragments
DBpedia's Triple Pattern FragmentsDBpedia's Triple Pattern Fragments
DBpedia's Triple Pattern Fragments
 
Distributed Affordance
Distributed AffordanceDistributed Affordance
Distributed Affordance
 
The web – A hypermedia story
The web – A hypermedia storyThe web – A hypermedia story
The web – A hypermedia story
 
Querying federations 
of Triple Pattern Fragments
Querying federations 
of Triple Pattern FragmentsQuerying federations 
of Triple Pattern Fragments
Querying federations 
of Triple Pattern Fragments
 
The Lonesome LOD Cloud
The Lonesome LOD CloudThe Lonesome LOD Cloud
The Lonesome LOD Cloud
 
2010 Sopac Cosugi
2010 Sopac Cosugi2010 Sopac Cosugi
2010 Sopac Cosugi
 
STACK OVERFLOW DATASET ANALYSIS
STACK OVERFLOW DATASET ANALYSISSTACK OVERFLOW DATASET ANALYSIS
STACK OVERFLOW DATASET ANALYSIS
 
(Re-)Discovering Lost Web Pages
(Re-)Discovering Lost Web Pages(Re-)Discovering Lost Web Pages
(Re-)Discovering Lost Web Pages
 
Toronto OpenRefine MeetUp Nov 2015
Toronto OpenRefine MeetUp Nov 2015Toronto OpenRefine MeetUp Nov 2015
Toronto OpenRefine MeetUp Nov 2015
 
Getting Started With The Talis Platform
Getting Started With The Talis PlatformGetting Started With The Talis Platform
Getting Started With The Talis Platform
 
SPARQL Query Forms
SPARQL Query FormsSPARQL Query Forms
SPARQL Query Forms
 
Tutorial Linked APIs
Tutorial Linked APIsTutorial Linked APIs
Tutorial Linked APIs
 
On the Persistence of Persistent Identifiers of the Scholarly Web
On the Persistence of Persistent Identifiers of the Scholarly WebOn the Persistence of Persistent Identifiers of the Scholarly Web
On the Persistence of Persistent Identifiers of the Scholarly Web
 
Full text search
Full text searchFull text search
Full text search
 
Querying the Web
Querying the WebQuerying the Web
Querying the Web
 
Designing RESTful APIs
Designing RESTful APIsDesigning RESTful APIs
Designing RESTful APIs
 
Demystifying Apache Spark
Demystifying Apache SparkDemystifying Apache Spark
Demystifying Apache Spark
 
A Spark-Based Intelligent Assistant: Making Data Exploration in Natural Langu...
A Spark-Based Intelligent Assistant: Making Data Exploration in Natural Langu...A Spark-Based Intelligent Assistant: Making Data Exploration in Natural Langu...
A Spark-Based Intelligent Assistant: Making Data Exploration in Natural Langu...
 
Sphinx
SphinxSphinx
Sphinx
 
Improving data interoperability in Python and R
Improving data interoperability in Python and RImproving data interoperability in Python and R
Improving data interoperability in Python and R
 

Viewers also liked

SAPS - Semantic AtomPub-based Services
SAPS - Semantic AtomPub-based ServicesSAPS - Semantic AtomPub-based Services
SAPS - Semantic AtomPub-based ServicesMarkus Lanthaler
 
A Semantic Description Language for RESTful Data Services to Combat Semaphobia
A Semantic Description Language for RESTful Data Services to Combat SemaphobiaA Semantic Description Language for RESTful Data Services to Combat Semaphobia
A Semantic Description Language for RESTful Data Services to Combat SemaphobiaMarkus Lanthaler
 
Aligning Web Services with the Semantic Web to Create a Global Read-Write Gra...
Aligning Web Services with the Semantic Web to Create a Global Read-Write Gra...Aligning Web Services with the Semantic Web to Create a Global Read-Write Gra...
Aligning Web Services with the Semantic Web to Create a Global Read-Write Gra...Markus Lanthaler
 
Adrs Presentation March 2008
Adrs Presentation March 2008Adrs Presentation March 2008
Adrs Presentation March 2008guestabd20
 
Semantic Web Services: State of the Art
Semantic Web Services: State of the ArtSemantic Web Services: State of the Art
Semantic Web Services: State of the ArtMarkus Lanthaler
 
RESTdesc – Efficient runtime service discovery and consumption
RESTdesc – Efficient runtime service discovery and consumptionRESTdesc – Efficient runtime service discovery and consumption
RESTdesc – Efficient runtime service discovery and consumptionRuben Verborgh
 
Hypermedia Cannot be the Engine
Hypermedia Cannot be the EngineHypermedia Cannot be the Engine
Hypermedia Cannot be the EngineRuben Verborgh
 
A Deep Dive into JSON-LD and Hydra
A Deep Dive into JSON-LD and HydraA Deep Dive into JSON-LD and Hydra
A Deep Dive into JSON-LD and HydraMarkus Lanthaler
 
End-to-end W3C APIs - tpac 2012
End-to-end W3C APIs - tpac 2012End-to-end W3C APIs - tpac 2012
End-to-end W3C APIs - tpac 2012Alexandre Morgaut
 
Web Standards adoption in the AR market
Web Standards adoption in the AR marketWeb Standards adoption in the AR market
Web Standards adoption in the AR marketRob Manson
 
LODeX: Schema Summarization and automatic SPARQL query generation for Linked ...
LODeX: Schema Summarization and automatic SPARQL query generation for Linked ...LODeX: Schema Summarization and automatic SPARQL query generation for Linked ...
LODeX: Schema Summarization and automatic SPARQL query generation for Linked ...Fabio Benedetti
 
Linked Data Generation Process
Linked Data Generation ProcessLinked Data Generation Process
Linked Data Generation ProcessLD4SC
 
What is Hydra?
What is Hydra?What is Hydra?
What is Hydra?Findwise
 
Lisp Macros in 20 Minutes (Featuring Clojure)
Lisp Macros in 20 Minutes (Featuring Clojure)Lisp Macros in 20 Minutes (Featuring Clojure)
Lisp Macros in 20 Minutes (Featuring Clojure)Phil Calçado
 
HTTP and Your Angry Dog
HTTP and Your Angry DogHTTP and Your Angry Dog
HTTP and Your Angry DogRoss Tuck
 
A Web of Things to Reduce Energy Wastage
A Web of Things to Reduce Energy WastageA Web of Things to Reduce Energy Wastage
A Web of Things to Reduce Energy WastageMarkus Lanthaler
 
Rest and the hypermedia constraint
Rest and the hypermedia constraintRest and the hypermedia constraint
Rest and the hypermedia constraintInviqa
 
The Web 3.0 is just around the corner. Be prepared!
The Web 3.0 is just around the corner. Be prepared!The Web 3.0 is just around the corner. Be prepared!
The Web 3.0 is just around the corner. Be prepared!Markus Lanthaler
 
Exploiting the query structure for efficient join ordering in SPARQL queries
Exploiting the query structure for efficient join ordering in SPARQL queriesExploiting the query structure for efficient join ordering in SPARQL queries
Exploiting the query structure for efficient join ordering in SPARQL queriesLuiz Henrique Zambom Santana
 

Viewers also liked (20)

SAPS - Semantic AtomPub-based Services
SAPS - Semantic AtomPub-based ServicesSAPS - Semantic AtomPub-based Services
SAPS - Semantic AtomPub-based Services
 
A Semantic Description Language for RESTful Data Services to Combat Semaphobia
A Semantic Description Language for RESTful Data Services to Combat SemaphobiaA Semantic Description Language for RESTful Data Services to Combat Semaphobia
A Semantic Description Language for RESTful Data Services to Combat Semaphobia
 
Aligning Web Services with the Semantic Web to Create a Global Read-Write Gra...
Aligning Web Services with the Semantic Web to Create a Global Read-Write Gra...Aligning Web Services with the Semantic Web to Create a Global Read-Write Gra...
Aligning Web Services with the Semantic Web to Create a Global Read-Write Gra...
 
Adrs Presentation March 2008
Adrs Presentation March 2008Adrs Presentation March 2008
Adrs Presentation March 2008
 
Semantic Web Services: State of the Art
Semantic Web Services: State of the ArtSemantic Web Services: State of the Art
Semantic Web Services: State of the Art
 
RESTdesc – Efficient runtime service discovery and consumption
RESTdesc – Efficient runtime service discovery and consumptionRESTdesc – Efficient runtime service discovery and consumption
RESTdesc – Efficient runtime service discovery and consumption
 
Hypermedia Cannot be the Engine
Hypermedia Cannot be the EngineHypermedia Cannot be the Engine
Hypermedia Cannot be the Engine
 
F-interop Meetup
F-interop MeetupF-interop Meetup
F-interop Meetup
 
A Deep Dive into JSON-LD and Hydra
A Deep Dive into JSON-LD and HydraA Deep Dive into JSON-LD and Hydra
A Deep Dive into JSON-LD and Hydra
 
End-to-end W3C APIs - tpac 2012
End-to-end W3C APIs - tpac 2012End-to-end W3C APIs - tpac 2012
End-to-end W3C APIs - tpac 2012
 
Web Standards adoption in the AR market
Web Standards adoption in the AR marketWeb Standards adoption in the AR market
Web Standards adoption in the AR market
 
LODeX: Schema Summarization and automatic SPARQL query generation for Linked ...
LODeX: Schema Summarization and automatic SPARQL query generation for Linked ...LODeX: Schema Summarization and automatic SPARQL query generation for Linked ...
LODeX: Schema Summarization and automatic SPARQL query generation for Linked ...
 
Linked Data Generation Process
Linked Data Generation ProcessLinked Data Generation Process
Linked Data Generation Process
 
What is Hydra?
What is Hydra?What is Hydra?
What is Hydra?
 
Lisp Macros in 20 Minutes (Featuring Clojure)
Lisp Macros in 20 Minutes (Featuring Clojure)Lisp Macros in 20 Minutes (Featuring Clojure)
Lisp Macros in 20 Minutes (Featuring Clojure)
 
HTTP and Your Angry Dog
HTTP and Your Angry DogHTTP and Your Angry Dog
HTTP and Your Angry Dog
 
A Web of Things to Reduce Energy Wastage
A Web of Things to Reduce Energy WastageA Web of Things to Reduce Energy Wastage
A Web of Things to Reduce Energy Wastage
 
Rest and the hypermedia constraint
Rest and the hypermedia constraintRest and the hypermedia constraint
Rest and the hypermedia constraint
 
The Web 3.0 is just around the corner. Be prepared!
The Web 3.0 is just around the corner. Be prepared!The Web 3.0 is just around the corner. Be prepared!
The Web 3.0 is just around the corner. Be prepared!
 
Exploiting the query structure for efficient join ordering in SPARQL queries
Exploiting the query structure for efficient join ordering in SPARQL queriesExploiting the query structure for efficient join ordering in SPARQL queries
Exploiting the query structure for efficient join ordering in SPARQL queries
 

Similar to Reasoned SPARQL

SAFE: Policy Aware SPARQL Query Federation Over RDF Data Cubes
SAFE: Policy Aware SPARQL Query Federation Over RDF Data CubesSAFE: Policy Aware SPARQL Query Federation Over RDF Data Cubes
SAFE: Policy Aware SPARQL Query Federation Over RDF Data CubesRatnesh Sahay
 
How to deploy Apache Spark in a multi-tenant, on-premises environment
How to deploy Apache Spark in a multi-tenant, on-premises environmentHow to deploy Apache Spark in a multi-tenant, on-premises environment
How to deploy Apache Spark in a multi-tenant, on-premises environmentBlueData, Inc.
 
Big Linked Data ETL Benchmark on Cloud Commodity Hardware
Big Linked Data ETL Benchmark on Cloud Commodity HardwareBig Linked Data ETL Benchmark on Cloud Commodity Hardware
Big Linked Data ETL Benchmark on Cloud Commodity HardwareLaurens De Vocht
 
Tutorial "An Introduction to SPARQL and Queries over Linked Data" Chapter 3 (...
Tutorial "An Introduction to SPARQL and Queries over Linked Data" Chapter 3 (...Tutorial "An Introduction to SPARQL and Queries over Linked Data" Chapter 3 (...
Tutorial "An Introduction to SPARQL and Queries over Linked Data" Chapter 3 (...Olaf Hartig
 
SAFE: Policy Aware SPARQL Query Federation Over RDF Data Cubes
SAFE: Policy Aware SPARQL Query Federation Over RDF Data CubesSAFE: Policy Aware SPARQL Query Federation Over RDF Data Cubes
SAFE: Policy Aware SPARQL Query Federation Over RDF Data CubesMuhammad Saleem
 
What’s New in the Berkeley Data Analytics Stack
What’s New in the Berkeley Data Analytics StackWhat’s New in the Berkeley Data Analytics Stack
What’s New in the Berkeley Data Analytics StackTuri, Inc.
 
Big Data Trend and Open Data
Big Data Trend and Open DataBig Data Trend and Open Data
Big Data Trend and Open DataJongwook Woo
 
Virtual Gov Day - IT Operations Breakout - Jennifer Green, R&D Scientist, Los...
Virtual Gov Day - IT Operations Breakout - Jennifer Green, R&D Scientist, Los...Virtual Gov Day - IT Operations Breakout - Jennifer Green, R&D Scientist, Los...
Virtual Gov Day - IT Operations Breakout - Jennifer Green, R&D Scientist, Los...Splunk
 
Scaling up with Cisco Big Data: Data + Science = Data Science
Scaling up with Cisco Big Data: Data + Science = Data ScienceScaling up with Cisco Big Data: Data + Science = Data Science
Scaling up with Cisco Big Data: Data + Science = Data ScienceeRic Choo
 
AMP Camp 5 Intro
AMP Camp 5 IntroAMP Camp 5 Intro
AMP Camp 5 Introjeykottalam
 
Introduction to Big data
Introduction to Big dataIntroduction to Big data
Introduction to Big datacthanopoulos
 
Countering Threats with the Elastic Stack at CERDEC/ARL
Countering Threats with the Elastic Stack at CERDEC/ARLCountering Threats with the Elastic Stack at CERDEC/ARL
Countering Threats with the Elastic Stack at CERDEC/ARLElasticsearch
 
ESWC2015 - Query Optimization for Clients of Linked Data Fragments
ESWC2015 - Query Optimization for Clients of Linked Data FragmentsESWC2015 - Query Optimization for Clients of Linked Data Fragments
ESWC2015 - Query Optimization for Clients of Linked Data FragmentsJoachim Van Herwegen
 
A Machine Learning Approach to SPARQL Query Performance Prediction
A Machine Learning Approach to SPARQL Query Performance PredictionA Machine Learning Approach to SPARQL Query Performance Prediction
A Machine Learning Approach to SPARQL Query Performance PredictionRakebul Hasan
 
Predicting query performance and explaining results to assist Linked Data con...
Predicting query performance and explaining results to assist Linked Data con...Predicting query performance and explaining results to assist Linked Data con...
Predicting query performance and explaining results to assist Linked Data con...Rakebul Hasan
 
Linked Open Data (LOD) part 2
Linked Open Data (LOD)  part 2Linked Open Data (LOD)  part 2
Linked Open Data (LOD) part 2IPLODProject
 
Big Data Processing Beyond MapReduce by Dr. Flavio Villanustre
Big Data Processing Beyond MapReduce by Dr. Flavio VillanustreBig Data Processing Beyond MapReduce by Dr. Flavio Villanustre
Big Data Processing Beyond MapReduce by Dr. Flavio VillanustreHPCC Systems
 
Data Integration Lecture Notes
Data Integration Lecture NotesData Integration Lecture Notes
Data Integration Lecture NotesSpyridon Safras
 

Similar to Reasoned SPARQL (20)

SAFE: Policy Aware SPARQL Query Federation Over RDF Data Cubes
SAFE: Policy Aware SPARQL Query Federation Over RDF Data CubesSAFE: Policy Aware SPARQL Query Federation Over RDF Data Cubes
SAFE: Policy Aware SPARQL Query Federation Over RDF Data Cubes
 
How to deploy Apache Spark in a multi-tenant, on-premises environment
How to deploy Apache Spark in a multi-tenant, on-premises environmentHow to deploy Apache Spark in a multi-tenant, on-premises environment
How to deploy Apache Spark in a multi-tenant, on-premises environment
 
Big Linked Data ETL Benchmark on Cloud Commodity Hardware
Big Linked Data ETL Benchmark on Cloud Commodity HardwareBig Linked Data ETL Benchmark on Cloud Commodity Hardware
Big Linked Data ETL Benchmark on Cloud Commodity Hardware
 
Tutorial "An Introduction to SPARQL and Queries over Linked Data" Chapter 3 (...
Tutorial "An Introduction to SPARQL and Queries over Linked Data" Chapter 3 (...Tutorial "An Introduction to SPARQL and Queries over Linked Data" Chapter 3 (...
Tutorial "An Introduction to SPARQL and Queries over Linked Data" Chapter 3 (...
 
SAFE: Policy Aware SPARQL Query Federation Over RDF Data Cubes
SAFE: Policy Aware SPARQL Query Federation Over RDF Data CubesSAFE: Policy Aware SPARQL Query Federation Over RDF Data Cubes
SAFE: Policy Aware SPARQL Query Federation Over RDF Data Cubes
 
What’s New in the Berkeley Data Analytics Stack
What’s New in the Berkeley Data Analytics StackWhat’s New in the Berkeley Data Analytics Stack
What’s New in the Berkeley Data Analytics Stack
 
Big Data Trend and Open Data
Big Data Trend and Open DataBig Data Trend and Open Data
Big Data Trend and Open Data
 
Virtual Gov Day - IT Operations Breakout - Jennifer Green, R&D Scientist, Los...
Virtual Gov Day - IT Operations Breakout - Jennifer Green, R&D Scientist, Los...Virtual Gov Day - IT Operations Breakout - Jennifer Green, R&D Scientist, Los...
Virtual Gov Day - IT Operations Breakout - Jennifer Green, R&D Scientist, Los...
 
Scaling up with Cisco Big Data: Data + Science = Data Science
Scaling up with Cisco Big Data: Data + Science = Data ScienceScaling up with Cisco Big Data: Data + Science = Data Science
Scaling up with Cisco Big Data: Data + Science = Data Science
 
Linked Data and Semantic Web Application Development by Peter Haase
Linked Data and Semantic Web Application Development by Peter HaaseLinked Data and Semantic Web Application Development by Peter Haase
Linked Data and Semantic Web Application Development by Peter Haase
 
AMP Camp 5 Intro
AMP Camp 5 IntroAMP Camp 5 Intro
AMP Camp 5 Intro
 
Introduction to Big data
Introduction to Big dataIntroduction to Big data
Introduction to Big data
 
Countering Threats with the Elastic Stack at CERDEC/ARL
Countering Threats with the Elastic Stack at CERDEC/ARLCountering Threats with the Elastic Stack at CERDEC/ARL
Countering Threats with the Elastic Stack at CERDEC/ARL
 
ESWC2015 - Query Optimization for Clients of Linked Data Fragments
ESWC2015 - Query Optimization for Clients of Linked Data FragmentsESWC2015 - Query Optimization for Clients of Linked Data Fragments
ESWC2015 - Query Optimization for Clients of Linked Data Fragments
 
A Machine Learning Approach to SPARQL Query Performance Prediction
A Machine Learning Approach to SPARQL Query Performance PredictionA Machine Learning Approach to SPARQL Query Performance Prediction
A Machine Learning Approach to SPARQL Query Performance Prediction
 
Predicting query performance and explaining results to assist Linked Data con...
Predicting query performance and explaining results to assist Linked Data con...Predicting query performance and explaining results to assist Linked Data con...
Predicting query performance and explaining results to assist Linked Data con...
 
Linked Open Data (LOD) part 2
Linked Open Data (LOD)  part 2Linked Open Data (LOD)  part 2
Linked Open Data (LOD) part 2
 
Big Data Processing Beyond MapReduce by Dr. Flavio Villanustre
Big Data Processing Beyond MapReduce by Dr. Flavio VillanustreBig Data Processing Beyond MapReduce by Dr. Flavio Villanustre
Big Data Processing Beyond MapReduce by Dr. Flavio Villanustre
 
Olap, expert system, data visualisation
Olap, expert system, data visualisationOlap, expert system, data visualisation
Olap, expert system, data visualisation
 
Data Integration Lecture Notes
Data Integration Lecture NotesData Integration Lecture Notes
Data Integration Lecture Notes
 

Reasoned SPARQL

  • 1. ELIS  –  Mul*media  Lab Reasoned SPARQL Sam Coppens, Miel Vander Sande, Ruben Verborgh, Erik Mannens, Rik Van de Walle,
  • 2.
  • 4. JACK BAUER INTERROGATION TECHNIQUE When asking politely just isn’t enough Reasoning on distributed data
  • 6.
  • 7. ELIS  –  Mul*media  Lab Goal: Reasoning as a Service Smart SPARQL agents outsource reasoning to appropriate infrastructure (client-side, server-side, or third party) Client Server / Data Provider Reasoning OWL QLOWL RL / EL
  • 8. ELIS  –  Mul*media  Lab Smart SPARQL Agent Goal: Reasoning as a Service Client Server / Data Provider Reasoning Reasoning Grid Goal: Reasoning as a Service Smart SPARQL agents outsource reasoning to appropriate infrastructure (client-side, server-side, or third party)
  • 9. ELIS  –  Mul*media  Lab Distributed Reasoning (LarKC) Identification Selection Transformation Reasoning Decision REASON <http://test.com/rules.n3> OVER { ?s ?p ?o } WHERE { ?s ?p ?o } Solution: ‘Reason’ Query Form
  • 10. ELIS  –  Mul*media  Lab SPARQL 1.1: Support for entailment regimes (RDFS, OWL) by means of BGP matching Data provider decides inference rules support With reasoned SPARQL, the data consumer choses the inference rules for reasoning
  • 11. ELIS  –  Mul*media  Lab Nested Queries SELECT ?child WHERE { :Jenna :child ?child . { REASON { { ?x :parent ?y } => { ?y :child ?x } . } OVER { ?s :parent ?o . } WHERE { ?s a :Person; :parent ?o . } } }
  • 12. ELIS  –  Mul*media  Lab • Workload Balancing REASON { { ?x foaf:knows ?y } => { ?y foaf:knows ?x } . } OVER { :Jenna foaf:knows ?person . } WHERE{ { SERVICE <http://example.org/sparql> { :Jenna foaf:knows ?person . } } UNION { SERVICE <http://example2.org/sparql> { :Jenna foaf:knows ?person . } } }
  • 13. ELIS  –  Mul*media  Lab Pitfalls Incomplete reasoning / errors like SPARQL Server-side vs. client-side reasoning probably OWL QL reasoning server-side BGP matching OWL RL and EL will happen client-side
  • 14. ELIS  –  Mul*media  Lab Distributed reasoning on top of distributed querying Reasoning as a service Use Cases End user Distributed Reasoning Framework Endpoints Endpoints Endpoints Client External Reasoner Endpoint
  • 15. ELIS  –  Mul*media  Lab Reasoning on distributed data SPARQL
  • 18. ELIS  –  Mul*media  Lab Sam Coppens, Miel Vander Sande, Ruben Verborgh, Erik Mannens, Rik Van de Walle, Reasoned SPARQL Using SPARQL agents to obtain answers through distribution and reasoning