FedX - Optimization Techniques for Federated Query Processing on Linked Dataaschwarte
The final slides of our talk about FedX at the 10th International Semantic Web Conference in Bonn. For details about FedX see http://www.fluidops.com/fedx/
"SPARQL Cheat Sheet" is a short collection of slides intended to act as a guide to SPARQL developers. It includes the syntax and structure of SPARQL queries, common SPARQL prefixes and functions, and help with RDF datasets.
The "SPARQL Cheat Sheet" is intended to accompany the SPARQL By Example slides available at http://www.cambridgesemantics.com/2008/09/sparql-by-example/ .
FedX - Optimization Techniques for Federated Query Processing on Linked Dataaschwarte
The final slides of our talk about FedX at the 10th International Semantic Web Conference in Bonn. For details about FedX see http://www.fluidops.com/fedx/
"SPARQL Cheat Sheet" is a short collection of slides intended to act as a guide to SPARQL developers. It includes the syntax and structure of SPARQL queries, common SPARQL prefixes and functions, and help with RDF datasets.
The "SPARQL Cheat Sheet" is intended to accompany the SPARQL By Example slides available at http://www.cambridgesemantics.com/2008/09/sparql-by-example/ .
HiBISCuS: Hypergraph-Based Source Selection for SPARQL Endpoint FederationMuhammad Saleem
Efficient federated query processing is of significant importance to tame the large amount of data available on the Web of Data. Previous works have focused on generating optimized query execution plans for fast result retrieval. However, devising source selection approaches beyond triple pattern-wise source selection has not received much attention. This work presents HiBISCuS, a novel hypergraph-based source selection approach to federated SPARQL querying. Our approach can be directly combined with existing SPARQL query federation engines to achieve the same recall while querying fewer data sources. We extend three well-known SPARQL query federation engines with HiBISCus and compare our extensions with the original approaches on FedBench. Our evaluation shows that HiBISCuS can efficiently reduce the total number of sources selected without losing recall. Moreover, our approach significantly reduces the execution time of the selected engines on most of the benchmark queries.
These slides are a brief update on the status of the work of the current SPARQL Working Group. "SPARQL 1.1" collectively refers to the upcoming versions of the SPARQL query language, SPARQL update language, and other deliverables of the 2nd (current) SPARQL Working Group.
Compare and contrast RDF triple stores and NoSQL: are triples stores NoSQL or not?
Talk given 2011-09-08 tot he BigData/NoSQL meetup at Bristol University.
Two graph data models : RDF and Property Graphsandyseaborne
Talk given at ApacheConEU Big Data 2015.
This talk describes the two common graph data approaches, RDF and Property Graphs. It concludes with observations about the different emphasis of each and where each is focused.
What is the fuzz on triple stores? Will triple stores eventually replace relational databases? This talk looks at the big picture, explains the technology and tries to look at the road ahead.
Talk at 3th Keystone Training School - Keyword Search in Big Linked Data - Institute for Software Technology and Interactive Systems, TU Wien, Austria, 2017
Wi2015 - Clustering of Linked Open Data - the LODeX toolLaura Po
Presentation of the tool LODeX (http://www.dbgroup.unimore.it/lodex2/testCluster) at the 2015 IEEE/WIC/ACM International Conference on Web Intelligence, Singapore, December 6-8, 2015
This is a lecture note #10 for my class of Graduate School of Yonsei University, Korea.
It describes SPARQL to retrieve and manipulate data stored in Resource Description Framework format
This presentation looks in detail at SPARQL (SPARQL Protocol and RDF Query Language) and introduces approaches for querying and updating semantic data. It covers the SPARQL algebra, the SPARQL protocol, and provides examples for reasoning over Linked Data. We use examples from the music domain, which can be directly tried out and ran over the MusicBrainz dataset. This includes gaining some familiarity with the RDFS and OWL languages, which allow developers to formulate generic and conceptual knowledge that can be exploited by automatic reasoning services in order to enhance the power of querying.
HiBISCuS: Hypergraph-Based Source Selection for SPARQL Endpoint FederationMuhammad Saleem
Efficient federated query processing is of significant importance to tame the large amount of data available on the Web of Data. Previous works have focused on generating optimized query execution plans for fast result retrieval. However, devising source selection approaches beyond triple pattern-wise source selection has not received much attention. This work presents HiBISCuS, a novel hypergraph-based source selection approach to federated SPARQL querying. Our approach can be directly combined with existing SPARQL query federation engines to achieve the same recall while querying fewer data sources. We extend three well-known SPARQL query federation engines with HiBISCus and compare our extensions with the original approaches on FedBench. Our evaluation shows that HiBISCuS can efficiently reduce the total number of sources selected without losing recall. Moreover, our approach significantly reduces the execution time of the selected engines on most of the benchmark queries.
These slides are a brief update on the status of the work of the current SPARQL Working Group. "SPARQL 1.1" collectively refers to the upcoming versions of the SPARQL query language, SPARQL update language, and other deliverables of the 2nd (current) SPARQL Working Group.
Compare and contrast RDF triple stores and NoSQL: are triples stores NoSQL or not?
Talk given 2011-09-08 tot he BigData/NoSQL meetup at Bristol University.
Two graph data models : RDF and Property Graphsandyseaborne
Talk given at ApacheConEU Big Data 2015.
This talk describes the two common graph data approaches, RDF and Property Graphs. It concludes with observations about the different emphasis of each and where each is focused.
What is the fuzz on triple stores? Will triple stores eventually replace relational databases? This talk looks at the big picture, explains the technology and tries to look at the road ahead.
Talk at 3th Keystone Training School - Keyword Search in Big Linked Data - Institute for Software Technology and Interactive Systems, TU Wien, Austria, 2017
Wi2015 - Clustering of Linked Open Data - the LODeX toolLaura Po
Presentation of the tool LODeX (http://www.dbgroup.unimore.it/lodex2/testCluster) at the 2015 IEEE/WIC/ACM International Conference on Web Intelligence, Singapore, December 6-8, 2015
This is a lecture note #10 for my class of Graduate School of Yonsei University, Korea.
It describes SPARQL to retrieve and manipulate data stored in Resource Description Framework format
This presentation looks in detail at SPARQL (SPARQL Protocol and RDF Query Language) and introduces approaches for querying and updating semantic data. It covers the SPARQL algebra, the SPARQL protocol, and provides examples for reasoning over Linked Data. We use examples from the music domain, which can be directly tried out and ran over the MusicBrainz dataset. This includes gaining some familiarity with the RDFS and OWL languages, which allow developers to formulate generic and conceptual knowledge that can be exploited by automatic reasoning services in order to enhance the power of querying.
SPARQL introduction and training (130+ slides with exercices)Thomas Francart
Full SPARQL training
Covers all SPARQL : basic graph patterns, FILTERs, functions, property paths, optional, negation, assignation, aggregation, subqueries, federated queries.
Does not cover except SPARQL updates.
Includes exercices on DBPedia.
CC BY license
Sesam4 project presentation sparql - april 2011Robert Engels
This slide set is a provided by the SESAM4 consortium as one out of three Technology Primers on Semantic Web technology. This Primer is on SPARQL and gives you a short introduction to its constructs followed by some examples. You can find the belonging slideset at youtube,
Sesam4 project presentation sparql - april 2011sesam4able
This slide set is a provided by the SESAM4 consortium as one out of three Technology Primers on Semantic Web technology. This Primer is on SPARQL and gives you a short introduction to its constructs followed by some examples. You can find the belonging slideset at youtube under SESAM4.
Re-using Media on the Web: Media fragment re-mixing and playoutMediaMixerCommunity
A number of novel application ideas will be introduced based on the media fragment creation, specification and rights management technologies. Semantic search and retrieval allows us to organize sets of fragments by topical or conceptual relevance. These fragment sets can then be played out in a non-linear fashion to create a new media re-mix. We look at a server-client implementation supporting Media Fragments, before allowing the participants to take the sets of media they have selected and create their own re-mix.
Learning Analytics : entre Promesses et RéalitéSerge Garlatti
Université Bretagne Pays de Loire, UTICE : LES LEARNING ANALYTICS : QUAND LE BIG DATA S’INTÉRESSE À L’ÉDUCATION.
https://utice.u-bretagneloire.fr/evenement/les-learning-analytics-quand-le-big-data-sinteresse-leducation
L’usage du numérique dans l’éducation permet d’accéder aujourd’hui à une multitude de données sur le comportement des étudiants : identité, interactions entre apprenants, interactions avec les plateformes et outils d’apprentissage, résultats aux évaluations... La collecte et l’exploitation de ces données permettent de mieux comprendre les processus d’apprentissage et ainsi d’adapter les parcours pédagogiques proposés pour en renforcer l’efficacité, mais aussi de personnaliser les apprentissages ou de développer des outils de pilotage des formations. Une communauté de chercheurs et d’enseignants se développe autour de ce que l’on appelle les learning analytics, ou l’analyse des données d’apprentissage. Ce séminaire basé sur les recherches et des retours d’expérience d’enseignants-chercheurs et de jeunes entreprises permettra de cerner les enjeux et les perspectives des learning analytics.
How to Create Map Views in the Odoo 17 ERPCeline George
The map views are useful for providing a geographical representation of data. They allow users to visualize and analyze the data in a more intuitive manner.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
How to Split Bills in the Odoo 17 POS ModuleCeline George
Bills have a main role in point of sale procedure. It will help to track sales, handling payments and giving receipts to customers. Bill splitting also has an important role in POS. For example, If some friends come together for dinner and if they want to divide the bill then it is possible by POS bill splitting. This slide will show how to split bills in odoo 17 POS.
Palestine last event orientationfvgnh .pptxRaedMohamed3
An EFL lesson about the current events in Palestine. It is intended to be for intermediate students who wish to increase their listening skills through a short lesson in power point.
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
3. SPARQL: SPARQL Protocol and RDF Query
Language
SPARQL
• pronounced "sparkle" [1]) is an RDF query language; its name
is a recursive acronym that stands for SPARQL Protocol and
RDF Query Language. It is standardized by the RDF Data
Access Working Group (DAWG) of the
World Wide Web Consortium, and is considered a component
of the semantic web.
• Initially released as a Candidate Recommendation in April
2006, but returned to Working Draft status in October 2006,
due to two open issues. [2] In June 2007, SPARQL advanced
to Candidate Recommendation once again. [3] On 12th
November 2007 the status of SPARQL changed into Proposed
Recommendation. [4] On 15th January 2008, SPARQL became
an official W3C Recommendation. [5]
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Computer Science Department
Semantic Web in Action
4. SPARQL: SPARQL Protocol and RDF Query
Language
SPARQL
=
• A Query Language
• A Result Form
• An Access Protocol
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Computer Science Department
Linked Data & Social Web
5. SPARQL: SPARQL Protocol and RDF Query
Language
The
Query Language: query forms
• « Select » clause returns all or subset of the
variables bound in a query pattern match
• « Construct » returns an RDF graph constructed by
substituting variables in a set of triple templates
• « Ask » returns a boolean indicating whether a query
pattern matches
• « Describe » returns an RDF graph that describe the
resources found
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Computer Science Department
Linked Data & Social Web
6. SPARQL: SPARQL Protocol and RDF Query
Language
«
Select » equivalent to « SQL Select » returns a
regular table
Select …
From …
Identify data sources to query
Where { … } The triple/graph pattern
to be matched against the
triple/graphs of RDF
A conjunction of triples
PREFIX
page 6
to declare the schema used in the query
Computer Science Department
Linked Data & Social Web
7. SPARQL: SPARQL Protocol and RDF Query
Language
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
SELECT ?name
FROM <http://example.org/foaf/aliceFoaf>
WHERE
{
?x foaf:name ?name
}
Result:
name
« Alice »
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Linked Data & Social Web
8. SPARQL: SPARQL Protocol and RDF Query
Language
PREFIX
PREFIX
PREFIX
PREFIX
foaf: <http://xmlns.com/foaf/0.1/>
: <http://dbpedia.org/resource/>
dbpedia2: <http://dbpedia.org/property/>
dbpedia: <http://dbpedia.org/>
SELECT distinct ?name ?birth ?person
FROM
<http://dbpedia.org/>
WHERE
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{
?person dbpedia2:birthPlace <http://dbpedia.org/resource/Berlin>.
?person dbpedia2:birth ?birth .
?person foaf:name ?name .
}
Computer Science Department
Semantic Web in Action
9. SPARQL: SPARQL Protocol and RDF Query
Language
SPARQL
results:
namebirthperson« ":Dru_Berrymore/birth/birth_date_and_age :Dru_Berrymore "Dru
Berrymore"@de:Dru_Berrymore/birth/birth_date_and_age :Dru_Berrymore "Walter
Benjamin"@de:Berlin :Walter_Benjamin "Walter Benjamin"@de:Germany
:Walter_Benjamin
Name
Birth
« Dru Berrymore »
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Person
10. SPARQL: SPARQL Protocol and RDF Query
Language
page 10
SELECT distinct ?name ?person
FROM
<http://dbpedia.org/>
WHERE
{
?person dbpedia2:birthPlace
<http://dbpedia.org/resource/Berlin> .
?person foaf:name ?name .
}
SELECT distinct ?name ?birth ?death ?person
FROM
<http://dbpedia.org/>
WHERE
{
?person dbpedia2:birthPlace
<http://dbpedia.org/resource/Berlin> .
?person dbpedia2:birth ?birth .
?person foaf:name ?name .
?person dbpedia2:death ?death.
}
Computer Science Department
Semantic Web in Action
11. SPARQL: SPARQL Protocol and RDF Query
Language
A
constraint, expressed by the keyword “FILTER”,
is a restriction on solutions over the whole group
in which the filter appears
PREFIX dc: <http://purl.org/dc/elements/1.1/>
PREFIX ns: <http://example.org/ns#>
SELECT ?title ?price
WHERE
{
?x ns:price ?price .
FILTER (?price < 30.5)
?x dc:title ?title .
}
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Computer Science Department
Linked Data & Social Web
12. SPARQL: SPARQL Protocol and RDF Query
Language
“regex”
matches only plain literals with no
language tag
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{
?x foaf:name ?name .
?x foaf:mbox ?mbox .
FILTER regex(?name, "Smith")
}
PREFIX dc: <http://purl.org/dc/elements/1.1/>
SELECT ?title
WHERE
{
?x dc:title ?title
FILTER regex(?title, "web", "i" ) }
Computer Science Department
Linked Data & Social Web
13. SPARQL: SPARQL Protocol and RDF Query
Language
Optional
parts of the graph pattern may be
specified syntactically with the “OPTIONAL”
keyword applied to a graph pattern
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SELECT distinct ?name ?birth ?death ?person
FROM
<http://dbpedia.org/>
WHERE
{ ?person dbpedia2:birthPlace
<http://dbpedia.org/resource/Berlin> .
?person dbpedia2:birth ?birth .
?person foaf:name ?name .
OPTIONAL {?person dbpedia2:death ?death}
}
Computer Science Department
Linked Data & Social Web
14. SPARQL: SPARQL Protocol and RDF Query
Language
Matching
alternative
• Pattern alternatives are syntactically specified with the
UNION keyword
SELECT distinct ?name ?birth ?death ?person
WHERE {
{?person dbpedia2:birthPlace
<http://dbpedia.org/resource/Berlin> }
UNION
{?person dbpedia2:death ?death}
?person foaf:name ?name .
?person dbpedia2:birth ?birth .
}
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Computer Science Department
Linked Data & Social Web
15. SPARQL: SPARQL Protocol and RDF Query
Language
Sequence
& Modify
• « Order By » to sort,
• « LIMIT » result number,
• « OFFSET » rank of first result
SELECT distinct ?name ?person
WHERE
{
?person dbpedia2:birthPlace <http://dbpedia.org/resource/Berlin>.
?person foaf:name ?name.
}
ORDER BY ?name LIMIT 20 OFFSET 20
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Linked Data & Social Web
16. SPARQL: SPARQL Protocol and RDF Query
Language
«
Construct »
• The CONSTRUCT query form returns a single RDF
graph specified by a graph template.
- The result is an RDF graph formed by taking each query
solution in the solution sequence, substituting for the
variables in the graph template, and combining the triples into
a single RDF graph by set union.
• Useful for aggregating data from multiple sources
and merging it into a local store (from Ingenta)
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Linked Data & Social Web
17. SPARQL: SPARQL Protocol and RDF Query
Language
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
FROM <http://molene.enstb.org/mlearning09/wpcontent/plugins/wp-rdfa/foaf.php
CONSTRUCT
{
?friend a foaf:Person;
foaf:name ?name;
foaf:homepage ?home.}
WHERE
{
?person foaf:mbox <mailto:ac@enstb.com>;
foaf:knows ?friend.
?friend foaf:name ?name;
foaf:homepage ?home.}
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Computer Science Department
Linked Data & Social Web
18. SPARQL: SPARQL Protocol and RDF Query
Language
ASK
• Returns a true/false value: test whether or not a query pattern
has a solution.
• No information is returned about the possible query solutions,
just whether or not a solution exists
• Is there data that looks like this? Do you have any information
about that? (from Ingenta)
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PREFIX foaf: <http://xmlns.com/foaf/0.1/>
ASK
WHERE {
?person a foaf:Person;
foaf:mbox <mailto:ab@telecom-bretagne>.
}
Computer Science Department
Semantic Web in Action
19. SPARQL: SPARQL Protocol and RDF Query
Language
DESCRIBE
• The DESCRIBE form returns a single result RDF
graph containing RDF data about resources.
• CONSTRUCT but with less control
- Tell me about this or things that look like this … but you
decide what’s relevant (from Ingenta)
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
DESCRIBE ?friend
WHERE {
?person foaf:mbox “mailto:ab@telecom-bretagne”;
foaf:knows ?friend.}
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Semantic Web in Action
20. SPARQL: SPARQL Protocol and RDF Query
Language
Applied
uses (from Ingenta)
• DESCRIBE for Prototyping
- DESCRIBE <http://example.org/someResource>
- Quickly assembling Uis, Web APIs
• SELECT for Indexing
- Building an ordering over some data ORDER BY, LIMIT
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Semantic Web in Action
21. SPARQL: SPARQL Protocol and RDF Query
Language
Applied
uses (from Ingenta)
• CONSTRUCT for transformation and also simple
inferencing
- CONSTRUCT could be the XSLT of RDF
- Currently limited by lack of expressions in CONSTRUCT
triple templates
• ASK for validation
• ASK – DESCRIBE – CONSTRUCT Pattern:
- Probe endpoint, Grab default view of data, Refine data extraction and/or
apply transformation
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Semantic Web in Action
22. SPARQL: SPARQL Protocol and RDF Query
Language
SPARQL
Protocol (from F. Gandon, INRIA)
• Sending queries and their results accross the web
Example
with HTTP binding
• GET /sparql/?query=<encoded query>
HTTP/1.1
Host: www.inria.fr
User-agent: my-sparql-client/0.1
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Semantic Web in Action
23. SPARQL: SPARQL Protocol and RDF Query
Language
Example
with SOAP binding (from F. Gandon)
<?xml version="1.0" encoding="UTF-8"?>
<soapenv:Envelope
xmlns:soapenv="http://www.w3.org/2003/05/soap-envelope/"
xmlns:xsd="http://www.w3.org/2001/XMLSchema"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<soapenv:Body>
<query-request xmlns="http://www.w3.org/2005/09/sparqlprotocol-types/#">
<query> SELECT ?x ?p ?y WHERE {?x ?p ?y} </query>
</query-request>
</soapenv:Body>
</soapenv:Envelope>
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Semantic Web in Action
24. SPARQL: SPARQL Protocol and RDF Query
Language
Access
to Data on the web
• http://dbpedia.org/snorql/
• http://dbpedia.org/sparql
• http://demo.openlinksw.com/rdfbrowser2/
• http://dataviewer.zitgist.com/
• Etc.
Twinkle : a sparql query tool
• http://www.ldodds.com/projects/twinkle
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Computer Science Department
Linked Data & Social Web
25. SPARQL: SPARQL Protocol and RDF Query
Language
Resources
• http://en.wikipedia.org/wiki/SPARQL
• http://www.w3.org/TR/rdf-sparql-query/
• http://jena.sourceforge.net/ARQ/Tutorial/
• http://esw.w3.org/topic/SparqlImplementations
• http://arc.semsol.org/home
• http://virtuoso.openlinksw.com/wiki/main/Main/
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