SlideShare ist ein Scribd-Unternehmen logo
1 von 1
Downloaden Sie, um offline zu lesen
Completeness Statements about RDF Data Sources
and Their Use for Query Answering
Fariz Darari
joint work with Werner Nutt, Giuseppe Pirrò, and Simon Razniewski
KRDB, Free University of Bozen-Bolzano, Italy

Context

Problem

Thousands of RDF data sources are today
available on the Web.
Machine-readable qualitative descriptions
of their content are crucial.
We focus on data completeness,
an important aspect of data quality.

Contributions

How to formalize and express in
a machine-readable way
completeness information
about RDF data sources?
How to leverage
such completeness information?

Completeness statement on the Web

1. Formal framework for expressing
completeness information.
2. Study of query completeness from
completeness information
in various settings.

Completeness statement on the Semantic Web
lv:lmdbdataset rdf:type void:Dataset.
lv:lmdbdataset c:hasComplStmt lv:st1.
lv:st1 c:hasPattern
[c:subject[spin:varName "m"]; c:predicate schema:actor; c:object[spin:varName "a"]].
lv:st1 c:hasCondition
[c:subject [spin:varName "m"]; c:predicate rdf:type; c:object schema:Movie].
lv:st1 c:hasCondition
[c:subject [spin:varName "m"]; c:predicate schema:director; c:object dbp:Tarantino].

Semantics of completeness statements
For each completeness statement, all the triple patterns defined
via hasPattern are collected into a set P1 and all the triple patterns defined
via hasCondition are collected into a set P2. A completeness statement is
interpreted as: CONSTRUCT {P1} WHERE {P1 . P2}
When a data source has a completeness statement (defined via
hasComplStmt), it means that if the query above is evaluated over
an “ideal” graph then all the results are in the data source.

Users visiting this source can prefer it
to other sources.

Checking query completeness
Given a query Q and a data source with completeness statements S:
1. Create a template answer graph GQ of Q.
2. Over GQ , evaluate all CONSTRUCT queries derived from S
3. Check whether GQ can be obtained after the evaluation.
If yes, the query is complete, otherwise might be incomplete.

However, the completeness
statement verified as complete is
only human readable!

Query completeness in a single data source scenario
@prefix
@prefix
@prefix
@prefix
@prefix
@prefix
@prefix
@prefix

c: <http://inf.unibz.it/ontologies/completeness#>
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
spin: <http://spinrdf.org/sp#>
void: <http://rdfs.org/ns/void#>
dv: <http://dbpedia.org/void/>
lv: <http://linkedmdb.org/void/>
dbp: <http://dbpedia.org/resource/>
schema: <http://schema.org>

dv:dbpdataset rdf:type void:Dataset;
dv:dbpdataset c:hasComplStmt dv:st1.
dv:st1 c:hasPattern [c:subject [spin:varName "m"];
c:predicate rdf:type; c:object schema:Movie
].
dv:st1 c:hasPattern [c:subject [spin:varName "m"];
c:predicate schema:director;c:object dbp:Tarantino].

Endpoint IRI
DBPe

lv:lmdbdataset rdf:type void:Dataset;
lv:lmdbdataset c:hasComplStmt lv:st1.
lv:st1 c:hasPattern [c:subject [spin:varName "m"];
c:predicate rdf:type; c:object schema:Movie
].
lv:st1 c:hasPattern [c:subject [spin:varName "m"];
c:predicate schema:director;c:object dbp:Tarantino ].
lv:lmdbdataset c:hasComplStmt lv:st2.
lv:st2 c:hasPattern
[c:subject[spin:varName "m"];
c:predicate schema:actor; c:object[spin:varName "a"]].
lv:st2 c:hasCondition [c:subject [spin:varName "m"];
c:predicate rdf:type; c:object schema:Movie].
lv:st2 c:hasCondition [c:subject [spin:varName "m"];
c:predicate schema:director; c:object dbp:Tarantino].

Select all the movies for which
Tarantino is the director and also an actor
SPARQL
endpoint

DBPedia is complete
for all Tarantino's movies

The answer is
incomplete

Endpoint IRI
LMDBe

SELECT ?m
SPARQL
WHERE {?m rdf:type schema:Movie. The answer is
endpoint
complete
?m schema:director dbp:Tarantino.
?m schema:actor dbp:Tarantino}
LinkedMDB is completeall Tarantino’s movies and
LMDB is complete for for all Tarantino's movies
Q
and also moviestheir actors. is an actor
all for which he

Extensions
SPARQL queries with OPT
Completeness with RDFS inference
Federated query completeness

Work In Progress
SPARQL queries with negations and comparisons

Live, Web-based CoRner
Empirical evaluation of query completeness checking

Why is DBpedia
not complete for the query ?
The completeness statement
in DBpedia says that
it is complete for Tarantino’s
movies (dv:st1). However, the
query asks about all movies for
which Tarantino is the director,
and also an actor.
It is not stated that DBpedia
includes all the actors of
Tarantino’s movies.
Therefore, DBpedia is possibly
not complete for this query.

Why is LinkedMDB
complete ?
The completeness statements in
LMDB say that they are complete
for Tarantino’s movies (lv:st1)
and also the actors (lv:st2).

Implementation

CoRner:
Completeness Reasoner
http://rdfcorner.wordpress.com

Weitere ähnliche Inhalte

Was ist angesagt?

Consuming Linked Data by Machines - WWW2010
Consuming Linked Data by Machines - WWW2010Consuming Linked Data by Machines - WWW2010
Consuming Linked Data by Machines - WWW2010Juan Sequeda
 
2010 06 ipaw_prv
2010 06 ipaw_prv2010 06 ipaw_prv
2010 06 ipaw_prvJun Zhao
 
The Semantic Web #10 - SPARQL
The Semantic Web #10 - SPARQLThe Semantic Web #10 - SPARQL
The Semantic Web #10 - SPARQLMyungjin Lee
 
Federated Query Formulation and Processing Through BioFed
Federated Query Formulation and Processing Through BioFedFederated Query Formulation and Processing Through BioFed
Federated Query Formulation and Processing Through BioFedMuhammad Saleem
 
An introduction to Semantic Web and Linked Data
An introduction to Semantic Web and Linked DataAn introduction to Semantic Web and Linked Data
An introduction to Semantic Web and Linked DataFabien Gandon
 
(Re-) Discovering Lost Web Pages
(Re-) Discovering Lost Web Pages(Re-) Discovering Lost Web Pages
(Re-) Discovering Lost Web PagesMichael Nelson
 
when the link makes sense
when the link makes sensewhen the link makes sense
when the link makes senseFabien Gandon
 
Efficient source selection for sparql endpoint federation
Efficient source selection for sparql endpoint federationEfficient source selection for sparql endpoint federation
Efficient source selection for sparql endpoint federationMuhammad Saleem
 
SPARQL and the Open Linked Data initiative
SPARQL and the Open Linked Data initiativeSPARQL and the Open Linked Data initiative
SPARQL and the Open Linked Data initiativeFulvio Corno
 
HiBISCuS: Hypergraph-Based Source Selection for SPARQL Endpoint Federation
HiBISCuS: Hypergraph-Based Source Selection for SPARQL Endpoint FederationHiBISCuS: Hypergraph-Based Source Selection for SPARQL Endpoint Federation
HiBISCuS: Hypergraph-Based Source Selection for SPARQL Endpoint FederationMuhammad Saleem
 
Introduction to Linked Data
Introduction to Linked DataIntroduction to Linked Data
Introduction to Linked DataThomas Meehan
 

Was ist angesagt? (20)

Web of data
Web of dataWeb of data
Web of data
 
Linked Data APIs (Funding Circle May 2015)
Linked Data APIs (Funding Circle May 2015)Linked Data APIs (Funding Circle May 2015)
Linked Data APIs (Funding Circle May 2015)
 
Fedora Migration Considerations
Fedora Migration ConsiderationsFedora Migration Considerations
Fedora Migration Considerations
 
Introduction to RDF Data Model
Introduction to RDF Data ModelIntroduction to RDF Data Model
Introduction to RDF Data Model
 
Consuming Linked Data by Machines - WWW2010
Consuming Linked Data by Machines - WWW2010Consuming Linked Data by Machines - WWW2010
Consuming Linked Data by Machines - WWW2010
 
2010 06 ipaw_prv
2010 06 ipaw_prv2010 06 ipaw_prv
2010 06 ipaw_prv
 
The Semantic Web #10 - SPARQL
The Semantic Web #10 - SPARQLThe Semantic Web #10 - SPARQL
The Semantic Web #10 - SPARQL
 
Rdf
RdfRdf
Rdf
 
West coastrollout
West coastrolloutWest coastrollout
West coastrollout
 
Aall denver 2010
Aall denver 2010Aall denver 2010
Aall denver 2010
 
Federated Query Formulation and Processing Through BioFed
Federated Query Formulation and Processing Through BioFedFederated Query Formulation and Processing Through BioFed
Federated Query Formulation and Processing Through BioFed
 
An introduction to Semantic Web and Linked Data
An introduction to Semantic Web and Linked DataAn introduction to Semantic Web and Linked Data
An introduction to Semantic Web and Linked Data
 
Test2
Test2Test2
Test2
 
(Re-) Discovering Lost Web Pages
(Re-) Discovering Lost Web Pages(Re-) Discovering Lost Web Pages
(Re-) Discovering Lost Web Pages
 
when the link makes sense
when the link makes sensewhen the link makes sense
when the link makes sense
 
Efficient source selection for sparql endpoint federation
Efficient source selection for sparql endpoint federationEfficient source selection for sparql endpoint federation
Efficient source selection for sparql endpoint federation
 
SPARQL and the Open Linked Data initiative
SPARQL and the Open Linked Data initiativeSPARQL and the Open Linked Data initiative
SPARQL and the Open Linked Data initiative
 
HiBISCuS: Hypergraph-Based Source Selection for SPARQL Endpoint Federation
HiBISCuS: Hypergraph-Based Source Selection for SPARQL Endpoint FederationHiBISCuS: Hypergraph-Based Source Selection for SPARQL Endpoint Federation
HiBISCuS: Hypergraph-Based Source Selection for SPARQL Endpoint Federation
 
Tutorial for RDF Graphs
Tutorial for RDF GraphsTutorial for RDF Graphs
Tutorial for RDF Graphs
 
Introduction to Linked Data
Introduction to Linked DataIntroduction to Linked Data
Introduction to Linked Data
 

Andere mochten auch

ESWC 2013 Poster: Representing and Querying Negative Knowledge in RDF
ESWC 2013 Poster: Representing and Querying Negative Knowledge in RDFESWC 2013 Poster: Representing and Querying Negative Knowledge in RDF
ESWC 2013 Poster: Representing and Querying Negative Knowledge in RDFFariz Darari
 
Query-Driven Management of Linked Data Quality
Query-Driven Management of Linked Data QualityQuery-Driven Management of Linked Data Quality
Query-Driven Management of Linked Data QualityFariz Darari
 
Managing Completeness of Web Data
Managing Completeness of Web DataManaging Completeness of Web Data
Managing Completeness of Web DataFariz Darari
 
Linked Data Quality Assessment – daQ and Luzzu
Linked Data Quality Assessment – daQ and LuzzuLinked Data Quality Assessment – daQ and Luzzu
Linked Data Quality Assessment – daQ and Luzzujerdeb
 
Linking Open Data with Drupal
Linking Open Data with DrupalLinking Open Data with Drupal
Linking Open Data with Drupalemmanuel_jamin
 
Martin Bardsley: Quality In Austerity-Indicators of Quality
Martin Bardsley: Quality In Austerity-Indicators of QualityMartin Bardsley: Quality In Austerity-Indicators of Quality
Martin Bardsley: Quality In Austerity-Indicators of QualityNuffield Trust
 
Datalift at SemWebPro
Datalift at SemWebProDatalift at SemWebPro
Datalift at SemWebProDatalift
 
Applied semantic technology and linked data
Applied semantic technology and linked dataApplied semantic technology and linked data
Applied semantic technology and linked dataWilliam Smith
 
Linked data for Enterprise Data Integration
Linked data for Enterprise Data IntegrationLinked data for Enterprise Data Integration
Linked data for Enterprise Data IntegrationSören Auer
 
20100614 ISWSA Keynote
20100614 ISWSA Keynote20100614 ISWSA Keynote
20100614 ISWSA KeynoteAxel Polleres
 
Expressing No-Value Information in RDF
Expressing No-Value Information in RDFExpressing No-Value Information in RDF
Expressing No-Value Information in RDFFariz Darari
 
On the Semantic Web, Completeness does Matter!
On the Semantic Web, Completeness does Matter!On the Semantic Web, Completeness does Matter!
On the Semantic Web, Completeness does Matter!Fariz Darari
 
CORNER: A Completeness Reasoner for SPARQL Queries over RDF Data Sources
CORNER: A Completeness Reasoner for SPARQL Queries over RDF Data SourcesCORNER: A Completeness Reasoner for SPARQL Queries over RDF Data Sources
CORNER: A Completeness Reasoner for SPARQL Queries over RDF Data SourcesFariz Darari
 
Semantic Web: "ten year" update
Semantic Web: "ten year" updateSemantic Web: "ten year" update
Semantic Web: "ten year" updateJames Hendler
 
Managing Completeness of Data
Managing Completeness of DataManaging Completeness of Data
Managing Completeness of DataFariz Darari
 
Expressing No-Value Information in RDF
Expressing No-Value Information in RDFExpressing No-Value Information in RDF
Expressing No-Value Information in RDFFariz Darari
 
"What is left to do?", Dublin Core 2012 Keynote
"What is left to do?", Dublin Core 2012 Keynote"What is left to do?", Dublin Core 2012 Keynote
"What is left to do?", Dublin Core 2012 KeynoteDan Brickley
 
Sieve - Data Quality and Fusion - LWDM2012
Sieve - Data Quality and Fusion - LWDM2012Sieve - Data Quality and Fusion - LWDM2012
Sieve - Data Quality and Fusion - LWDM2012Pablo Mendes
 

Andere mochten auch (20)

ESWC 2013 Poster: Representing and Querying Negative Knowledge in RDF
ESWC 2013 Poster: Representing and Querying Negative Knowledge in RDFESWC 2013 Poster: Representing and Querying Negative Knowledge in RDF
ESWC 2013 Poster: Representing and Querying Negative Knowledge in RDF
 
Query-Driven Management of Linked Data Quality
Query-Driven Management of Linked Data QualityQuery-Driven Management of Linked Data Quality
Query-Driven Management of Linked Data Quality
 
Managing Completeness of Web Data
Managing Completeness of Web DataManaging Completeness of Web Data
Managing Completeness of Web Data
 
Linked Data Quality Assessment – daQ and Luzzu
Linked Data Quality Assessment – daQ and LuzzuLinked Data Quality Assessment – daQ and Luzzu
Linked Data Quality Assessment – daQ and Luzzu
 
Linking Open Data with Drupal
Linking Open Data with DrupalLinking Open Data with Drupal
Linking Open Data with Drupal
 
Martin Bardsley: Quality In Austerity-Indicators of Quality
Martin Bardsley: Quality In Austerity-Indicators of QualityMartin Bardsley: Quality In Austerity-Indicators of Quality
Martin Bardsley: Quality In Austerity-Indicators of Quality
 
Datalift at SemWebPro
Datalift at SemWebProDatalift at SemWebPro
Datalift at SemWebPro
 
Applied semantic technology and linked data
Applied semantic technology and linked dataApplied semantic technology and linked data
Applied semantic technology and linked data
 
LDQ 2014 DQ Methodology
LDQ 2014 DQ MethodologyLDQ 2014 DQ Methodology
LDQ 2014 DQ Methodology
 
Amrapali Zaveri Defense
Amrapali Zaveri DefenseAmrapali Zaveri Defense
Amrapali Zaveri Defense
 
Linked data for Enterprise Data Integration
Linked data for Enterprise Data IntegrationLinked data for Enterprise Data Integration
Linked data for Enterprise Data Integration
 
20100614 ISWSA Keynote
20100614 ISWSA Keynote20100614 ISWSA Keynote
20100614 ISWSA Keynote
 
Expressing No-Value Information in RDF
Expressing No-Value Information in RDFExpressing No-Value Information in RDF
Expressing No-Value Information in RDF
 
On the Semantic Web, Completeness does Matter!
On the Semantic Web, Completeness does Matter!On the Semantic Web, Completeness does Matter!
On the Semantic Web, Completeness does Matter!
 
CORNER: A Completeness Reasoner for SPARQL Queries over RDF Data Sources
CORNER: A Completeness Reasoner for SPARQL Queries over RDF Data SourcesCORNER: A Completeness Reasoner for SPARQL Queries over RDF Data Sources
CORNER: A Completeness Reasoner for SPARQL Queries over RDF Data Sources
 
Semantic Web: "ten year" update
Semantic Web: "ten year" updateSemantic Web: "ten year" update
Semantic Web: "ten year" update
 
Managing Completeness of Data
Managing Completeness of DataManaging Completeness of Data
Managing Completeness of Data
 
Expressing No-Value Information in RDF
Expressing No-Value Information in RDFExpressing No-Value Information in RDF
Expressing No-Value Information in RDF
 
"What is left to do?", Dublin Core 2012 Keynote
"What is left to do?", Dublin Core 2012 Keynote"What is left to do?", Dublin Core 2012 Keynote
"What is left to do?", Dublin Core 2012 Keynote
 
Sieve - Data Quality and Fusion - LWDM2012
Sieve - Data Quality and Fusion - LWDM2012Sieve - Data Quality and Fusion - LWDM2012
Sieve - Data Quality and Fusion - LWDM2012
 

Ähnlich wie Poster - Completeness Statements about RDF Data Sources and Their Use for Query Answering

A hands on overview of the semantic web
A hands on overview of the semantic webA hands on overview of the semantic web
A hands on overview of the semantic webMarakana Inc.
 
2009 0807 Lod Gmod
2009 0807 Lod Gmod2009 0807 Lod Gmod
2009 0807 Lod GmodJun Zhao
 
RDF Stream Processing and the role of Semantics
RDF Stream Processing and the role of SemanticsRDF Stream Processing and the role of Semantics
RDF Stream Processing and the role of SemanticsJean-Paul Calbimonte
 
Data Integration And Visualization
Data Integration And VisualizationData Integration And Visualization
Data Integration And VisualizationIvan Ermilov
 
Inference on the Semantic Web
Inference on the Semantic WebInference on the Semantic Web
Inference on the Semantic WebMyungjin Lee
 
State of the Semantic Web
State of the Semantic WebState of the Semantic Web
State of the Semantic WebIvan Herman
 
A Hands On Overview Of The Semantic Web
A Hands On Overview Of The Semantic WebA Hands On Overview Of The Semantic Web
A Hands On Overview Of The Semantic WebShamod Lacoul
 
SemanticWeb Nuts 'n Bolts
SemanticWeb Nuts 'n BoltsSemanticWeb Nuts 'n Bolts
SemanticWeb Nuts 'n BoltsRinke Hoekstra
 
2011 4IZ440 Semantic Web – RDF, SPARQL, and software APIs
2011 4IZ440 Semantic Web – RDF, SPARQL, and software APIs2011 4IZ440 Semantic Web – RDF, SPARQL, and software APIs
2011 4IZ440 Semantic Web – RDF, SPARQL, and software APIsJosef Petrák
 
A Little SPARQL in your Analytics
A Little SPARQL in your AnalyticsA Little SPARQL in your Analytics
A Little SPARQL in your AnalyticsDr. Neil Brittliff
 
Linked data 101: Getting Caught in the Semantic Web
Linked data 101: Getting Caught in the Semantic Web Linked data 101: Getting Caught in the Semantic Web
Linked data 101: Getting Caught in the Semantic Web Morgan Briles
 
Sustainable queryable access to Linked Data
Sustainable queryable access to Linked DataSustainable queryable access to Linked Data
Sustainable queryable access to Linked DataRuben Verborgh
 
Semantic Web
Semantic WebSemantic Web
Semantic Webhardchiu
 
Usage of Linked Data: Introduction and Application Scenarios
Usage of Linked Data: Introduction and Application ScenariosUsage of Linked Data: Introduction and Application Scenarios
Usage of Linked Data: Introduction and Application ScenariosEUCLID project
 

Ähnlich wie Poster - Completeness Statements about RDF Data Sources and Their Use for Query Answering (20)

Timbuctoo 2 EASY
Timbuctoo 2 EASYTimbuctoo 2 EASY
Timbuctoo 2 EASY
 
Linked Data Fragments
Linked Data FragmentsLinked Data Fragments
Linked Data Fragments
 
A hands on overview of the semantic web
A hands on overview of the semantic webA hands on overview of the semantic web
A hands on overview of the semantic web
 
2009 0807 Lod Gmod
2009 0807 Lod Gmod2009 0807 Lod Gmod
2009 0807 Lod Gmod
 
RDF Stream Processing and the role of Semantics
RDF Stream Processing and the role of SemanticsRDF Stream Processing and the role of Semantics
RDF Stream Processing and the role of Semantics
 
Data Integration And Visualization
Data Integration And VisualizationData Integration And Visualization
Data Integration And Visualization
 
Hacia la Internet del Futuro: Web Semántica y Open Linked Data, Parte 2
Hacia la Internet del Futuro: Web Semántica y Open Linked Data, Parte 2Hacia la Internet del Futuro: Web Semántica y Open Linked Data, Parte 2
Hacia la Internet del Futuro: Web Semántica y Open Linked Data, Parte 2
 
Inference on the Semantic Web
Inference on the Semantic WebInference on the Semantic Web
Inference on the Semantic Web
 
Data in RDF
Data in RDFData in RDF
Data in RDF
 
State of the Semantic Web
State of the Semantic WebState of the Semantic Web
State of the Semantic Web
 
Bio2RDF@BH2010
Bio2RDF@BH2010Bio2RDF@BH2010
Bio2RDF@BH2010
 
A Hands On Overview Of The Semantic Web
A Hands On Overview Of The Semantic WebA Hands On Overview Of The Semantic Web
A Hands On Overview Of The Semantic Web
 
SemanticWeb Nuts 'n Bolts
SemanticWeb Nuts 'n BoltsSemanticWeb Nuts 'n Bolts
SemanticWeb Nuts 'n Bolts
 
How RDFa works
How RDFa worksHow RDFa works
How RDFa works
 
2011 4IZ440 Semantic Web – RDF, SPARQL, and software APIs
2011 4IZ440 Semantic Web – RDF, SPARQL, and software APIs2011 4IZ440 Semantic Web – RDF, SPARQL, and software APIs
2011 4IZ440 Semantic Web – RDF, SPARQL, and software APIs
 
A Little SPARQL in your Analytics
A Little SPARQL in your AnalyticsA Little SPARQL in your Analytics
A Little SPARQL in your Analytics
 
Linked data 101: Getting Caught in the Semantic Web
Linked data 101: Getting Caught in the Semantic Web Linked data 101: Getting Caught in the Semantic Web
Linked data 101: Getting Caught in the Semantic Web
 
Sustainable queryable access to Linked Data
Sustainable queryable access to Linked DataSustainable queryable access to Linked Data
Sustainable queryable access to Linked Data
 
Semantic Web
Semantic WebSemantic Web
Semantic Web
 
Usage of Linked Data: Introduction and Application Scenarios
Usage of Linked Data: Introduction and Application ScenariosUsage of Linked Data: Introduction and Application Scenarios
Usage of Linked Data: Introduction and Application Scenarios
 

Mehr von Fariz Darari

Data X Museum - Hari Museum Internasional 2022 - WMID
Data X Museum - Hari Museum Internasional 2022 - WMIDData X Museum - Hari Museum Internasional 2022 - WMID
Data X Museum - Hari Museum Internasional 2022 - WMIDFariz Darari
 
[PUBLIC] quiz-01-midterm-solutions.pdf
[PUBLIC] quiz-01-midterm-solutions.pdf[PUBLIC] quiz-01-midterm-solutions.pdf
[PUBLIC] quiz-01-midterm-solutions.pdfFariz Darari
 
Free AI Kit - Game Theory
Free AI Kit - Game TheoryFree AI Kit - Game Theory
Free AI Kit - Game TheoryFariz Darari
 
Neural Networks and Deep Learning: An Intro
Neural Networks and Deep Learning: An IntroNeural Networks and Deep Learning: An Intro
Neural Networks and Deep Learning: An IntroFariz Darari
 
NLP guest lecture: How to get text to confess what knowledge it has
NLP guest lecture: How to get text to confess what knowledge it hasNLP guest lecture: How to get text to confess what knowledge it has
NLP guest lecture: How to get text to confess what knowledge it hasFariz Darari
 
Supply and Demand - AI Talents
Supply and Demand - AI TalentsSupply and Demand - AI Talents
Supply and Demand - AI TalentsFariz Darari
 
Basic Python Programming: Part 01 and Part 02
Basic Python Programming: Part 01 and Part 02Basic Python Programming: Part 01 and Part 02
Basic Python Programming: Part 01 and Part 02Fariz Darari
 
AI in education done properly
AI in education done properlyAI in education done properly
AI in education done properlyFariz Darari
 
Artificial Neural Networks: Pointers
Artificial Neural Networks: PointersArtificial Neural Networks: Pointers
Artificial Neural Networks: PointersFariz Darari
 
Open Tridharma at ICACSIS 2019
Open Tridharma at ICACSIS 2019Open Tridharma at ICACSIS 2019
Open Tridharma at ICACSIS 2019Fariz Darari
 
Defense Slides of Avicenna Wisesa - PROWD
Defense Slides of Avicenna Wisesa - PROWDDefense Slides of Avicenna Wisesa - PROWD
Defense Slides of Avicenna Wisesa - PROWDFariz Darari
 
Seminar Laporan Aktualisasi - Tridharma Terbuka - Fariz Darari
Seminar Laporan Aktualisasi - Tridharma Terbuka - Fariz DarariSeminar Laporan Aktualisasi - Tridharma Terbuka - Fariz Darari
Seminar Laporan Aktualisasi - Tridharma Terbuka - Fariz DarariFariz Darari
 
Foundations of Programming - Java OOP
Foundations of Programming - Java OOPFoundations of Programming - Java OOP
Foundations of Programming - Java OOPFariz Darari
 
Recursion in Python
Recursion in PythonRecursion in Python
Recursion in PythonFariz Darari
 
[ISWC 2013] Completeness statements about RDF data sources and their use for ...
[ISWC 2013] Completeness statements about RDF data sources and their use for ...[ISWC 2013] Completeness statements about RDF data sources and their use for ...
[ISWC 2013] Completeness statements about RDF data sources and their use for ...Fariz Darari
 
Testing in Python: doctest and unittest (Updated)
Testing in Python: doctest and unittest (Updated)Testing in Python: doctest and unittest (Updated)
Testing in Python: doctest and unittest (Updated)Fariz Darari
 
Testing in Python: doctest and unittest
Testing in Python: doctest and unittestTesting in Python: doctest and unittest
Testing in Python: doctest and unittestFariz Darari
 
Dissertation Defense - Managing and Consuming Completeness Information for RD...
Dissertation Defense - Managing and Consuming Completeness Information for RD...Dissertation Defense - Managing and Consuming Completeness Information for RD...
Dissertation Defense - Managing and Consuming Completeness Information for RD...Fariz Darari
 
Research Writing - 2018.07.18
Research Writing - 2018.07.18Research Writing - 2018.07.18
Research Writing - 2018.07.18Fariz Darari
 
KOI - Knowledge Of Incidents - SemEval 2018
KOI - Knowledge Of Incidents - SemEval 2018KOI - Knowledge Of Incidents - SemEval 2018
KOI - Knowledge Of Incidents - SemEval 2018Fariz Darari
 

Mehr von Fariz Darari (20)

Data X Museum - Hari Museum Internasional 2022 - WMID
Data X Museum - Hari Museum Internasional 2022 - WMIDData X Museum - Hari Museum Internasional 2022 - WMID
Data X Museum - Hari Museum Internasional 2022 - WMID
 
[PUBLIC] quiz-01-midterm-solutions.pdf
[PUBLIC] quiz-01-midterm-solutions.pdf[PUBLIC] quiz-01-midterm-solutions.pdf
[PUBLIC] quiz-01-midterm-solutions.pdf
 
Free AI Kit - Game Theory
Free AI Kit - Game TheoryFree AI Kit - Game Theory
Free AI Kit - Game Theory
 
Neural Networks and Deep Learning: An Intro
Neural Networks and Deep Learning: An IntroNeural Networks and Deep Learning: An Intro
Neural Networks and Deep Learning: An Intro
 
NLP guest lecture: How to get text to confess what knowledge it has
NLP guest lecture: How to get text to confess what knowledge it hasNLP guest lecture: How to get text to confess what knowledge it has
NLP guest lecture: How to get text to confess what knowledge it has
 
Supply and Demand - AI Talents
Supply and Demand - AI TalentsSupply and Demand - AI Talents
Supply and Demand - AI Talents
 
Basic Python Programming: Part 01 and Part 02
Basic Python Programming: Part 01 and Part 02Basic Python Programming: Part 01 and Part 02
Basic Python Programming: Part 01 and Part 02
 
AI in education done properly
AI in education done properlyAI in education done properly
AI in education done properly
 
Artificial Neural Networks: Pointers
Artificial Neural Networks: PointersArtificial Neural Networks: Pointers
Artificial Neural Networks: Pointers
 
Open Tridharma at ICACSIS 2019
Open Tridharma at ICACSIS 2019Open Tridharma at ICACSIS 2019
Open Tridharma at ICACSIS 2019
 
Defense Slides of Avicenna Wisesa - PROWD
Defense Slides of Avicenna Wisesa - PROWDDefense Slides of Avicenna Wisesa - PROWD
Defense Slides of Avicenna Wisesa - PROWD
 
Seminar Laporan Aktualisasi - Tridharma Terbuka - Fariz Darari
Seminar Laporan Aktualisasi - Tridharma Terbuka - Fariz DarariSeminar Laporan Aktualisasi - Tridharma Terbuka - Fariz Darari
Seminar Laporan Aktualisasi - Tridharma Terbuka - Fariz Darari
 
Foundations of Programming - Java OOP
Foundations of Programming - Java OOPFoundations of Programming - Java OOP
Foundations of Programming - Java OOP
 
Recursion in Python
Recursion in PythonRecursion in Python
Recursion in Python
 
[ISWC 2013] Completeness statements about RDF data sources and their use for ...
[ISWC 2013] Completeness statements about RDF data sources and their use for ...[ISWC 2013] Completeness statements about RDF data sources and their use for ...
[ISWC 2013] Completeness statements about RDF data sources and their use for ...
 
Testing in Python: doctest and unittest (Updated)
Testing in Python: doctest and unittest (Updated)Testing in Python: doctest and unittest (Updated)
Testing in Python: doctest and unittest (Updated)
 
Testing in Python: doctest and unittest
Testing in Python: doctest and unittestTesting in Python: doctest and unittest
Testing in Python: doctest and unittest
 
Dissertation Defense - Managing and Consuming Completeness Information for RD...
Dissertation Defense - Managing and Consuming Completeness Information for RD...Dissertation Defense - Managing and Consuming Completeness Information for RD...
Dissertation Defense - Managing and Consuming Completeness Information for RD...
 
Research Writing - 2018.07.18
Research Writing - 2018.07.18Research Writing - 2018.07.18
Research Writing - 2018.07.18
 
KOI - Knowledge Of Incidents - SemEval 2018
KOI - Knowledge Of Incidents - SemEval 2018KOI - Knowledge Of Incidents - SemEval 2018
KOI - Knowledge Of Incidents - SemEval 2018
 

Kürzlich hochgeladen

Boost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfBoost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfsudhanshuwaghmare1
 
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...apidays
 
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...apidays
 
MS Copilot expands with MS Graph connectors
MS Copilot expands with MS Graph connectorsMS Copilot expands with MS Graph connectors
MS Copilot expands with MS Graph connectorsNanddeep Nachan
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FMESafe Software
 
Exploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone ProcessorsExploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone Processorsdebabhi2
 
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, AdobeApidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobeapidays
 
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemkeProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemkeProduct Anonymous
 
Architecting Cloud Native Applications
Architecting Cloud Native ApplicationsArchitecting Cloud Native Applications
Architecting Cloud Native ApplicationsWSO2
 
CNIC Information System with Pakdata Cf In Pakistan
CNIC Information System with Pakdata Cf In PakistanCNIC Information System with Pakdata Cf In Pakistan
CNIC Information System with Pakdata Cf In Pakistandanishmna97
 
DBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor PresentationDBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor PresentationDropbox
 
[BuildWithAI] Introduction to Gemini.pdf
[BuildWithAI] Introduction to Gemini.pdf[BuildWithAI] Introduction to Gemini.pdf
[BuildWithAI] Introduction to Gemini.pdfSandro Moreira
 
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...apidays
 
Exploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with MilvusExploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with MilvusZilliz
 
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ..."I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...Zilliz
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FMESafe Software
 
presentation ICT roal in 21st century education
presentation ICT roal in 21st century educationpresentation ICT roal in 21st century education
presentation ICT roal in 21st century educationjfdjdjcjdnsjd
 
FWD Group - Insurer Innovation Award 2024
FWD Group - Insurer Innovation Award 2024FWD Group - Insurer Innovation Award 2024
FWD Group - Insurer Innovation Award 2024The Digital Insurer
 
AWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of TerraformAWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of TerraformAndrey Devyatkin
 
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024Victor Rentea
 

Kürzlich hochgeladen (20)

Boost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfBoost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdf
 
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
 
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
 
MS Copilot expands with MS Graph connectors
MS Copilot expands with MS Graph connectorsMS Copilot expands with MS Graph connectors
MS Copilot expands with MS Graph connectors
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
 
Exploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone ProcessorsExploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone Processors
 
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, AdobeApidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
 
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemkeProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
 
Architecting Cloud Native Applications
Architecting Cloud Native ApplicationsArchitecting Cloud Native Applications
Architecting Cloud Native Applications
 
CNIC Information System with Pakdata Cf In Pakistan
CNIC Information System with Pakdata Cf In PakistanCNIC Information System with Pakdata Cf In Pakistan
CNIC Information System with Pakdata Cf In Pakistan
 
DBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor PresentationDBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor Presentation
 
[BuildWithAI] Introduction to Gemini.pdf
[BuildWithAI] Introduction to Gemini.pdf[BuildWithAI] Introduction to Gemini.pdf
[BuildWithAI] Introduction to Gemini.pdf
 
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
 
Exploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with MilvusExploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with Milvus
 
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ..."I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
 
presentation ICT roal in 21st century education
presentation ICT roal in 21st century educationpresentation ICT roal in 21st century education
presentation ICT roal in 21st century education
 
FWD Group - Insurer Innovation Award 2024
FWD Group - Insurer Innovation Award 2024FWD Group - Insurer Innovation Award 2024
FWD Group - Insurer Innovation Award 2024
 
AWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of TerraformAWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of Terraform
 
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
 

Poster - Completeness Statements about RDF Data Sources and Their Use for Query Answering

  • 1. Completeness Statements about RDF Data Sources and Their Use for Query Answering Fariz Darari joint work with Werner Nutt, Giuseppe Pirrò, and Simon Razniewski KRDB, Free University of Bozen-Bolzano, Italy Context Problem Thousands of RDF data sources are today available on the Web. Machine-readable qualitative descriptions of their content are crucial. We focus on data completeness, an important aspect of data quality. Contributions How to formalize and express in a machine-readable way completeness information about RDF data sources? How to leverage such completeness information? Completeness statement on the Web 1. Formal framework for expressing completeness information. 2. Study of query completeness from completeness information in various settings. Completeness statement on the Semantic Web lv:lmdbdataset rdf:type void:Dataset. lv:lmdbdataset c:hasComplStmt lv:st1. lv:st1 c:hasPattern [c:subject[spin:varName "m"]; c:predicate schema:actor; c:object[spin:varName "a"]]. lv:st1 c:hasCondition [c:subject [spin:varName "m"]; c:predicate rdf:type; c:object schema:Movie]. lv:st1 c:hasCondition [c:subject [spin:varName "m"]; c:predicate schema:director; c:object dbp:Tarantino]. Semantics of completeness statements For each completeness statement, all the triple patterns defined via hasPattern are collected into a set P1 and all the triple patterns defined via hasCondition are collected into a set P2. A completeness statement is interpreted as: CONSTRUCT {P1} WHERE {P1 . P2} When a data source has a completeness statement (defined via hasComplStmt), it means that if the query above is evaluated over an “ideal” graph then all the results are in the data source. Users visiting this source can prefer it to other sources. Checking query completeness Given a query Q and a data source with completeness statements S: 1. Create a template answer graph GQ of Q. 2. Over GQ , evaluate all CONSTRUCT queries derived from S 3. Check whether GQ can be obtained after the evaluation. If yes, the query is complete, otherwise might be incomplete. However, the completeness statement verified as complete is only human readable! Query completeness in a single data source scenario @prefix @prefix @prefix @prefix @prefix @prefix @prefix @prefix c: <http://inf.unibz.it/ontologies/completeness#> rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> spin: <http://spinrdf.org/sp#> void: <http://rdfs.org/ns/void#> dv: <http://dbpedia.org/void/> lv: <http://linkedmdb.org/void/> dbp: <http://dbpedia.org/resource/> schema: <http://schema.org> dv:dbpdataset rdf:type void:Dataset; dv:dbpdataset c:hasComplStmt dv:st1. dv:st1 c:hasPattern [c:subject [spin:varName "m"]; c:predicate rdf:type; c:object schema:Movie ]. dv:st1 c:hasPattern [c:subject [spin:varName "m"]; c:predicate schema:director;c:object dbp:Tarantino]. Endpoint IRI DBPe lv:lmdbdataset rdf:type void:Dataset; lv:lmdbdataset c:hasComplStmt lv:st1. lv:st1 c:hasPattern [c:subject [spin:varName "m"]; c:predicate rdf:type; c:object schema:Movie ]. lv:st1 c:hasPattern [c:subject [spin:varName "m"]; c:predicate schema:director;c:object dbp:Tarantino ]. lv:lmdbdataset c:hasComplStmt lv:st2. lv:st2 c:hasPattern [c:subject[spin:varName "m"]; c:predicate schema:actor; c:object[spin:varName "a"]]. lv:st2 c:hasCondition [c:subject [spin:varName "m"]; c:predicate rdf:type; c:object schema:Movie]. lv:st2 c:hasCondition [c:subject [spin:varName "m"]; c:predicate schema:director; c:object dbp:Tarantino]. Select all the movies for which Tarantino is the director and also an actor SPARQL endpoint DBPedia is complete for all Tarantino's movies The answer is incomplete Endpoint IRI LMDBe SELECT ?m SPARQL WHERE {?m rdf:type schema:Movie. The answer is endpoint complete ?m schema:director dbp:Tarantino. ?m schema:actor dbp:Tarantino} LinkedMDB is completeall Tarantino’s movies and LMDB is complete for for all Tarantino's movies Q and also moviestheir actors. is an actor all for which he Extensions SPARQL queries with OPT Completeness with RDFS inference Federated query completeness Work In Progress SPARQL queries with negations and comparisons Live, Web-based CoRner Empirical evaluation of query completeness checking Why is DBpedia not complete for the query ? The completeness statement in DBpedia says that it is complete for Tarantino’s movies (dv:st1). However, the query asks about all movies for which Tarantino is the director, and also an actor. It is not stated that DBpedia includes all the actors of Tarantino’s movies. Therefore, DBpedia is possibly not complete for this query. Why is LinkedMDB complete ? The completeness statements in LMDB say that they are complete for Tarantino’s movies (lv:st1) and also the actors (lv:st2). Implementation CoRner: Completeness Reasoner http://rdfcorner.wordpress.com