SlideShare una empresa de Scribd logo
1 de 18
1.1 What’s coming and what might be coming? May, 2010 Latest at http://www.slideshare.net/LeeFeigenbaum/sparql2-status Lee Feigenbaum, Co-chair, SPARQL Working Group lee@thefigtrees.net
Disclaimer The SPARQL Working Group has not yet decided many of the technical questions surveyed in these slides. All examples are subject to change; please do not construe them as indicators or endorsements of specific technical designs/decisions. All opinions are Lee Feigenbaum’s alone.
Naming SPARQL 1.1 is the collective name of the work produced by the current SPARQL Working Group. The actual components being worked on are known as:SPARQL 1.1 QuerySPARQL 1.1 Update SPARQL 1.1 Service Description …
Where are we now? Today August 2010 March 2009 ??? Last Call and beyond of core SPARQL specifications July 2009 FPWD of SPARQL New Features and Rationales document October 2009 FPWD of core SPARQL specifications
Overview
Projected Expressions Select expressions other than variables (literals, functions on literals and variables, etc.) SELECT (?price* ?qty AS ?total_price) WHERE {  … }
Aggregates À la SQL aggregates (MIN, MAX, COUNT, AVG, SUM etc.) Issues around: Aggregates and error values Grouping by expressions SELECT (MIN(?price) AS ?min_price)… WHERE { … } GROUP BY ?item
Subqueries Nested queries allow multiple queries to be combined into one.  SELECT ?article ?authorWHERE {   ?article ex:author ?author .  {     SELECT ?article WHERE {      … ?article …    } ORDER BY … LIMIT …  }}
Negation Supplant the mystifying OPTIONAL/!bound method of negation with a dedicated construct Issues around: Filter semantics vs. set-difference semantics Graph pattern operators vs. filter functions SELECT … WHERE {   ?person a foaf:Person . MINUS{     ?person foaf:mbox ?email  } }
Service Description A standard discovery mechanism and vocabulary for describing the capabilities, extensions, data sets, and more for a SPARQL endpoint Discovery. How can a client find the RDF that describes a SPARQL endpoint at a particular URI? Description. What predicates, classes, values, etc. should a client expect to find (and be able to query) once it locates a service description?
Update Language Based on the SPARQL Update member submission Batch insert & delete Insert & delete based on triple patterns Graph management (creation, removal) Issues around: Defining a formal model for update Graph stores vs. RDF data sets Return codes
Update Protocol The ability to issue SPARQL/Update language statements via a standard protocol (e.g. via HTTP POST) Issues around:  Security  Response HTTP codes
HTTP RDF update (RESTful) Where appropriate, map HTTP requests to SPARQL/Update operations DELETE /foo/g1 …-> DELETE DATA FROM ex:g1 … Issues around: Which mappings to include? Are graphs information resources?
Property Paths Support arbitrary-length predicate paths in triple patterns – “regular expressions” on predicates? Query hierarchical structures such as RDF collections Issues around: Duplicates and cycles in paths Negated path segments SELECT … WHERE {   ?person foaf:knows+ ?network . }
Basic Federated Query Initial scaffolding for authoring federated SPARQL queries Add a keyword to explicitly target portions of a query to specific endpoints Issues around: SERVICE and variables? Is federated query its own document? SELECT … WHERE {  … SERVICE ex:books {    …  } }
Entailment Regime Semantics SPARQL/Query 1.0 defines a mechanism to extend SPARQL semantics for additional entailment regimes Use this mechanism to define the semantics of SPARQL queries for: RDF Schema OWL fragments RIF rule sets …
Common Functions Extend the set of functions that SPARQL engines must support to include some of… Common string functions (e.g. substr) Common date/time/datetime functions Logical functions (COALESCE, IF, …?) Limited discussion to date about which functions to include
Get Involved Join.  Email team-sparql-chairs@w3.org Follow.  WG materials at http://www.w3.org/2009/sparql/wiki/ Comment.  Public feedback at public-rdf-dawg-comments@w3.org Use.  Discuss SPARQL at public-sparql-dev@w3.org

Más contenido relacionado

La actualidad más candente

SPARQL in a nutshell
SPARQL in a nutshellSPARQL in a nutshell
SPARQL in a nutshellFabien Gandon
 
WebTech Tutorial Querying DBPedia
WebTech Tutorial Querying DBPediaWebTech Tutorial Querying DBPedia
WebTech Tutorial Querying DBPediaKatrien Verbert
 
Linking the world with Python and Semantics
Linking the world with Python and SemanticsLinking the world with Python and Semantics
Linking the world with Python and SemanticsTatiana Al-Chueyr
 
An Introduction to SPARQL
An Introduction to SPARQLAn Introduction to SPARQL
An Introduction to SPARQLOlaf Hartig
 
Two graph data models : RDF and Property Graphs
Two graph data models : RDF and Property GraphsTwo graph data models : RDF and Property Graphs
Two graph data models : RDF and Property Graphsandyseaborne
 
SPARQL Query Verbalization for Explaining Semantic Search Engine Queries
SPARQL Query Verbalization for Explaining Semantic Search Engine QueriesSPARQL Query Verbalization for Explaining Semantic Search Engine Queries
SPARQL Query Verbalization for Explaining Semantic Search Engine QueriesBasil Ell
 
The Semantics of SPARQL
The Semantics of SPARQLThe Semantics of SPARQL
The Semantics of SPARQLOlaf Hartig
 
Federation and Navigation in SPARQL 1.1
Federation and Navigation in SPARQL 1.1Federation and Navigation in SPARQL 1.1
Federation and Navigation in SPARQL 1.1net2-project
 
RDF Tutorial - SPARQL 20091031
RDF Tutorial - SPARQL 20091031RDF Tutorial - SPARQL 20091031
RDF Tutorial - SPARQL 20091031kwangsub kim
 
070517 Jena
070517 Jena070517 Jena
070517 Jenayuhana
 
RDF Validation Future work and applications
RDF Validation Future work and applicationsRDF Validation Future work and applications
RDF Validation Future work and applicationsJose Emilio Labra Gayo
 
Sparql semantic information retrieval by
Sparql semantic information retrieval bySparql semantic information retrieval by
Sparql semantic information retrieval byIJNSA Journal
 
F# for functional enthusiasts
F# for functional enthusiastsF# for functional enthusiasts
F# for functional enthusiastsJack Fox
 

La actualidad más candente (20)

SPARQL in a nutshell
SPARQL in a nutshellSPARQL in a nutshell
SPARQL in a nutshell
 
WebTech Tutorial Querying DBPedia
WebTech Tutorial Querying DBPediaWebTech Tutorial Querying DBPedia
WebTech Tutorial Querying DBPedia
 
Linking the world with Python and Semantics
Linking the world with Python and SemanticsLinking the world with Python and Semantics
Linking the world with Python and Semantics
 
An Introduction to SPARQL
An Introduction to SPARQLAn Introduction to SPARQL
An Introduction to SPARQL
 
4 sw architectures and sparql
4 sw architectures and sparql4 sw architectures and sparql
4 sw architectures and sparql
 
SPARQL Tutorial
SPARQL TutorialSPARQL Tutorial
SPARQL Tutorial
 
Two graph data models : RDF and Property Graphs
Two graph data models : RDF and Property GraphsTwo graph data models : RDF and Property Graphs
Two graph data models : RDF and Property Graphs
 
SPARQL Query Verbalization for Explaining Semantic Search Engine Queries
SPARQL Query Verbalization for Explaining Semantic Search Engine QueriesSPARQL Query Verbalization for Explaining Semantic Search Engine Queries
SPARQL Query Verbalization for Explaining Semantic Search Engine Queries
 
Jena Programming
Jena ProgrammingJena Programming
Jena Programming
 
The Semantics of SPARQL
The Semantics of SPARQLThe Semantics of SPARQL
The Semantics of SPARQL
 
Federation and Navigation in SPARQL 1.1
Federation and Navigation in SPARQL 1.1Federation and Navigation in SPARQL 1.1
Federation and Navigation in SPARQL 1.1
 
RDF Tutorial - SPARQL 20091031
RDF Tutorial - SPARQL 20091031RDF Tutorial - SPARQL 20091031
RDF Tutorial - SPARQL 20091031
 
SPIN in Five Slides
SPIN in Five SlidesSPIN in Five Slides
SPIN in Five Slides
 
Introduction to SPARQL
Introduction to SPARQLIntroduction to SPARQL
Introduction to SPARQL
 
Introduction to R
Introduction to RIntroduction to R
Introduction to R
 
070517 Jena
070517 Jena070517 Jena
070517 Jena
 
RDF Validation Future work and applications
RDF Validation Future work and applicationsRDF Validation Future work and applications
RDF Validation Future work and applications
 
Sparql semantic information retrieval by
Sparql semantic information retrieval bySparql semantic information retrieval by
Sparql semantic information retrieval by
 
F# for functional enthusiasts
F# for functional enthusiastsF# for functional enthusiasts
F# for functional enthusiasts
 
LISP: Data types in lisp
LISP: Data types in lispLISP: Data types in lisp
LISP: Data types in lisp
 

Similar a SPARQL 1.1 Status

What;s Coming In SPARQL2?
What;s Coming In SPARQL2?What;s Coming In SPARQL2?
What;s Coming In SPARQL2?LeeFeigenbaum
 
A year on the Semantic Web @ W3C
A year on the Semantic Web @ W3CA year on the Semantic Web @ W3C
A year on the Semantic Web @ W3CIvan Herman
 
SPARQLing Services
SPARQLing ServicesSPARQLing Services
SPARQLing ServicesLeigh Dodds
 
SPARQL and SQL: technical aspects and synergy
SPARQL and SQL: technical aspects and synergySPARQL and SQL: technical aspects and synergy
SPARQL and SQL: technical aspects and synergyYannis Kalfoglou
 
The Semantic Web #10 - SPARQL
The Semantic Web #10 - SPARQLThe Semantic Web #10 - SPARQL
The Semantic Web #10 - SPARQLMyungjin Lee
 
Apache® Spark™ 1.6 presented by Databricks co-founder Patrick Wendell
Apache® Spark™ 1.6 presented by Databricks co-founder Patrick WendellApache® Spark™ 1.6 presented by Databricks co-founder Patrick Wendell
Apache® Spark™ 1.6 presented by Databricks co-founder Patrick WendellDatabricks
 
Swap For Dummies Rsp 2007 11 29
Swap For Dummies Rsp 2007 11 29Swap For Dummies Rsp 2007 11 29
Swap For Dummies Rsp 2007 11 29Julie Allinson
 
Overview of the SPARQL-Generate language and latest developments
Overview of the SPARQL-Generate language and latest developmentsOverview of the SPARQL-Generate language and latest developments
Overview of the SPARQL-Generate language and latest developmentsMaxime Lefrançois
 
Data Integration And Visualization
Data Integration And VisualizationData Integration And Visualization
Data Integration And VisualizationIvan Ermilov
 
Talis Platform: A Linked Data Engine
Talis Platform: A Linked Data EngineTalis Platform: A Linked Data Engine
Talis Platform: A Linked Data EngineLeigh Dodds
 
Querying the Semantic Web with SPARQL
Querying the Semantic Web with SPARQLQuerying the Semantic Web with SPARQL
Querying the Semantic Web with SPARQLEmanuele Della Valle
 
SPARQL Query Forms
SPARQL Query FormsSPARQL Query Forms
SPARQL Query FormsLeigh Dodds
 
Spark SQL In Depth www.syedacademy.com
Spark SQL In Depth www.syedacademy.comSpark SQL In Depth www.syedacademy.com
Spark SQL In Depth www.syedacademy.comSyed Hadoop
 
Apache Spark - Intro to Large-scale recommendations with Apache Spark and Python
Apache Spark - Intro to Large-scale recommendations with Apache Spark and PythonApache Spark - Intro to Large-scale recommendations with Apache Spark and Python
Apache Spark - Intro to Large-scale recommendations with Apache Spark and PythonChristian Perone
 
1 extreme performance - part i
1   extreme performance - part i1   extreme performance - part i
1 extreme performance - part isqlserver.co.il
 
Exceptions are the Norm: Dealing with Bad Actors in ETL
Exceptions are the Norm: Dealing with Bad Actors in ETLExceptions are the Norm: Dealing with Bad Actors in ETL
Exceptions are the Norm: Dealing with Bad Actors in ETLDatabricks
 
Automating the Use of Web APIs through Lightweight Semantics
Automating the Use of Web APIs through Lightweight SemanticsAutomating the Use of Web APIs through Lightweight Semantics
Automating the Use of Web APIs through Lightweight Semanticsmmaleshkova
 
Oracle Fundamental and PL-SQL.docx
Oracle Fundamental and PL-SQL.docxOracle Fundamental and PL-SQL.docx
Oracle Fundamental and PL-SQL.docxChandan Kumar
 
Using Apache Spark as ETL engine. Pros and Cons
Using Apache Spark as ETL engine. Pros and Cons          Using Apache Spark as ETL engine. Pros and Cons
Using Apache Spark as ETL engine. Pros and Cons Provectus
 

Similar a SPARQL 1.1 Status (20)

What;s Coming In SPARQL2?
What;s Coming In SPARQL2?What;s Coming In SPARQL2?
What;s Coming In SPARQL2?
 
A year on the Semantic Web @ W3C
A year on the Semantic Web @ W3CA year on the Semantic Web @ W3C
A year on the Semantic Web @ W3C
 
SPARQLing Services
SPARQLing ServicesSPARQLing Services
SPARQLing Services
 
SPARQL and SQL: technical aspects and synergy
SPARQL and SQL: technical aspects and synergySPARQL and SQL: technical aspects and synergy
SPARQL and SQL: technical aspects and synergy
 
The Semantic Web #10 - SPARQL
The Semantic Web #10 - SPARQLThe Semantic Web #10 - SPARQL
The Semantic Web #10 - SPARQL
 
Apache® Spark™ 1.6 presented by Databricks co-founder Patrick Wendell
Apache® Spark™ 1.6 presented by Databricks co-founder Patrick WendellApache® Spark™ 1.6 presented by Databricks co-founder Patrick Wendell
Apache® Spark™ 1.6 presented by Databricks co-founder Patrick Wendell
 
Swap For Dummies Rsp 2007 11 29
Swap For Dummies Rsp 2007 11 29Swap For Dummies Rsp 2007 11 29
Swap For Dummies Rsp 2007 11 29
 
Overview of the SPARQL-Generate language and latest developments
Overview of the SPARQL-Generate language and latest developmentsOverview of the SPARQL-Generate language and latest developments
Overview of the SPARQL-Generate language and latest developments
 
Web Spa
Web SpaWeb Spa
Web Spa
 
Data Integration And Visualization
Data Integration And VisualizationData Integration And Visualization
Data Integration And Visualization
 
Talis Platform: A Linked Data Engine
Talis Platform: A Linked Data EngineTalis Platform: A Linked Data Engine
Talis Platform: A Linked Data Engine
 
Querying the Semantic Web with SPARQL
Querying the Semantic Web with SPARQLQuerying the Semantic Web with SPARQL
Querying the Semantic Web with SPARQL
 
SPARQL Query Forms
SPARQL Query FormsSPARQL Query Forms
SPARQL Query Forms
 
Spark SQL In Depth www.syedacademy.com
Spark SQL In Depth www.syedacademy.comSpark SQL In Depth www.syedacademy.com
Spark SQL In Depth www.syedacademy.com
 
Apache Spark - Intro to Large-scale recommendations with Apache Spark and Python
Apache Spark - Intro to Large-scale recommendations with Apache Spark and PythonApache Spark - Intro to Large-scale recommendations with Apache Spark and Python
Apache Spark - Intro to Large-scale recommendations with Apache Spark and Python
 
1 extreme performance - part i
1   extreme performance - part i1   extreme performance - part i
1 extreme performance - part i
 
Exceptions are the Norm: Dealing with Bad Actors in ETL
Exceptions are the Norm: Dealing with Bad Actors in ETLExceptions are the Norm: Dealing with Bad Actors in ETL
Exceptions are the Norm: Dealing with Bad Actors in ETL
 
Automating the Use of Web APIs through Lightweight Semantics
Automating the Use of Web APIs through Lightweight SemanticsAutomating the Use of Web APIs through Lightweight Semantics
Automating the Use of Web APIs through Lightweight Semantics
 
Oracle Fundamental and PL-SQL.docx
Oracle Fundamental and PL-SQL.docxOracle Fundamental and PL-SQL.docx
Oracle Fundamental and PL-SQL.docx
 
Using Apache Spark as ETL engine. Pros and Cons
Using Apache Spark as ETL engine. Pros and Cons          Using Apache Spark as ETL engine. Pros and Cons
Using Apache Spark as ETL engine. Pros and Cons
 

Más de LeeFeigenbaum

Data Segmenting in Anzo
Data Segmenting in AnzoData Segmenting in Anzo
Data Segmenting in AnzoLeeFeigenbaum
 
Intro to the Semantic Web Landscape - 2011
Intro to the Semantic Web Landscape - 2011Intro to the Semantic Web Landscape - 2011
Intro to the Semantic Web Landscape - 2011LeeFeigenbaum
 
Evolution Towards Web 3.0: The Semantic Web
Evolution Towards Web 3.0: The Semantic WebEvolution Towards Web 3.0: The Semantic Web
Evolution Towards Web 3.0: The Semantic WebLeeFeigenbaum
 
Taking the Tech out of SemTech
Taking the Tech out of SemTechTaking the Tech out of SemTech
Taking the Tech out of SemTechLeeFeigenbaum
 
CSHALS 2010 W3C Semanic Web Tutorial
CSHALS 2010 W3C Semanic Web TutorialCSHALS 2010 W3C Semanic Web Tutorial
CSHALS 2010 W3C Semanic Web TutorialLeeFeigenbaum
 
Semantic Web Landscape 2009
Semantic Web Landscape 2009Semantic Web Landscape 2009
Semantic Web Landscape 2009LeeFeigenbaum
 

Más de LeeFeigenbaum (6)

Data Segmenting in Anzo
Data Segmenting in AnzoData Segmenting in Anzo
Data Segmenting in Anzo
 
Intro to the Semantic Web Landscape - 2011
Intro to the Semantic Web Landscape - 2011Intro to the Semantic Web Landscape - 2011
Intro to the Semantic Web Landscape - 2011
 
Evolution Towards Web 3.0: The Semantic Web
Evolution Towards Web 3.0: The Semantic WebEvolution Towards Web 3.0: The Semantic Web
Evolution Towards Web 3.0: The Semantic Web
 
Taking the Tech out of SemTech
Taking the Tech out of SemTechTaking the Tech out of SemTech
Taking the Tech out of SemTech
 
CSHALS 2010 W3C Semanic Web Tutorial
CSHALS 2010 W3C Semanic Web TutorialCSHALS 2010 W3C Semanic Web Tutorial
CSHALS 2010 W3C Semanic Web Tutorial
 
Semantic Web Landscape 2009
Semantic Web Landscape 2009Semantic Web Landscape 2009
Semantic Web Landscape 2009
 

Último

08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking MenDelhi Call girls
 
CNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of ServiceCNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of Servicegiselly40
 
Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...Enterprise Knowledge
 
Powerful Google developer tools for immediate impact! (2023-24 C)
Powerful Google developer tools for immediate impact! (2023-24 C)Powerful Google developer tools for immediate impact! (2023-24 C)
Powerful Google developer tools for immediate impact! (2023-24 C)wesley chun
 
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024The Digital Insurer
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking MenDelhi Call girls
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountPuma Security, LLC
 
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Igalia
 
Artificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and MythsArtificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and MythsJoaquim Jorge
 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationSafe Software
 
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...apidays
 
How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonetsnaman860154
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreternaman860154
 
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptxEIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptxEarley Information Science
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024Rafal Los
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerThousandEyes
 
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Miguel Araújo
 
Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsHandwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsMaria Levchenko
 
Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024The Digital Insurer
 
What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?Antenna Manufacturer Coco
 

Último (20)

08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
 
CNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of ServiceCNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of Service
 
Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...
 
Powerful Google developer tools for immediate impact! (2023-24 C)
Powerful Google developer tools for immediate impact! (2023-24 C)Powerful Google developer tools for immediate impact! (2023-24 C)
Powerful Google developer tools for immediate impact! (2023-24 C)
 
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path Mount
 
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
 
Artificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and MythsArtificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and Myths
 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
 
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
 
How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonets
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreter
 
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptxEIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
 
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
 
Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsHandwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed texts
 
Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024
 
What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?
 

SPARQL 1.1 Status

  • 1. 1.1 What’s coming and what might be coming? May, 2010 Latest at http://www.slideshare.net/LeeFeigenbaum/sparql2-status Lee Feigenbaum, Co-chair, SPARQL Working Group lee@thefigtrees.net
  • 2. Disclaimer The SPARQL Working Group has not yet decided many of the technical questions surveyed in these slides. All examples are subject to change; please do not construe them as indicators or endorsements of specific technical designs/decisions. All opinions are Lee Feigenbaum’s alone.
  • 3. Naming SPARQL 1.1 is the collective name of the work produced by the current SPARQL Working Group. The actual components being worked on are known as:SPARQL 1.1 QuerySPARQL 1.1 Update SPARQL 1.1 Service Description …
  • 4. Where are we now? Today August 2010 March 2009 ??? Last Call and beyond of core SPARQL specifications July 2009 FPWD of SPARQL New Features and Rationales document October 2009 FPWD of core SPARQL specifications
  • 6. Projected Expressions Select expressions other than variables (literals, functions on literals and variables, etc.) SELECT (?price* ?qty AS ?total_price) WHERE { … }
  • 7. Aggregates À la SQL aggregates (MIN, MAX, COUNT, AVG, SUM etc.) Issues around: Aggregates and error values Grouping by expressions SELECT (MIN(?price) AS ?min_price)… WHERE { … } GROUP BY ?item
  • 8. Subqueries Nested queries allow multiple queries to be combined into one. SELECT ?article ?authorWHERE { ?article ex:author ?author . { SELECT ?article WHERE { … ?article … } ORDER BY … LIMIT … }}
  • 9. Negation Supplant the mystifying OPTIONAL/!bound method of negation with a dedicated construct Issues around: Filter semantics vs. set-difference semantics Graph pattern operators vs. filter functions SELECT … WHERE { ?person a foaf:Person . MINUS{ ?person foaf:mbox ?email } }
  • 10. Service Description A standard discovery mechanism and vocabulary for describing the capabilities, extensions, data sets, and more for a SPARQL endpoint Discovery. How can a client find the RDF that describes a SPARQL endpoint at a particular URI? Description. What predicates, classes, values, etc. should a client expect to find (and be able to query) once it locates a service description?
  • 11. Update Language Based on the SPARQL Update member submission Batch insert & delete Insert & delete based on triple patterns Graph management (creation, removal) Issues around: Defining a formal model for update Graph stores vs. RDF data sets Return codes
  • 12. Update Protocol The ability to issue SPARQL/Update language statements via a standard protocol (e.g. via HTTP POST) Issues around: Security Response HTTP codes
  • 13. HTTP RDF update (RESTful) Where appropriate, map HTTP requests to SPARQL/Update operations DELETE /foo/g1 …-> DELETE DATA FROM ex:g1 … Issues around: Which mappings to include? Are graphs information resources?
  • 14. Property Paths Support arbitrary-length predicate paths in triple patterns – “regular expressions” on predicates? Query hierarchical structures such as RDF collections Issues around: Duplicates and cycles in paths Negated path segments SELECT … WHERE { ?person foaf:knows+ ?network . }
  • 15. Basic Federated Query Initial scaffolding for authoring federated SPARQL queries Add a keyword to explicitly target portions of a query to specific endpoints Issues around: SERVICE and variables? Is federated query its own document? SELECT … WHERE { … SERVICE ex:books { … } }
  • 16. Entailment Regime Semantics SPARQL/Query 1.0 defines a mechanism to extend SPARQL semantics for additional entailment regimes Use this mechanism to define the semantics of SPARQL queries for: RDF Schema OWL fragments RIF rule sets …
  • 17. Common Functions Extend the set of functions that SPARQL engines must support to include some of… Common string functions (e.g. substr) Common date/time/datetime functions Logical functions (COALESCE, IF, …?) Limited discussion to date about which functions to include
  • 18. Get Involved Join. Email team-sparql-chairs@w3.org Follow. WG materials at http://www.w3.org/2009/sparql/wiki/ Comment. Public feedback at public-rdf-dawg-comments@w3.org Use. Discuss SPARQL at public-sparql-dev@w3.org

Notas del editor

  1. http://www.w3.org/Submission/SPARQL-Update/
  2. http://www.w3.org/Submission/SPARQL-Update/
  3. http://www.w3.org/Submission/SPARQL-Update/