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Semantic WebSPARQL

Gerd Groner, Matthias Thimm

{groener,thimm}@uni-koblenz.de

Institute for Web Science and Technologies (WeST)University of Koblenz-Landau

July 15, 2013

Gerd Groner, Matthias Thimm Semantic Web 1 / 56

Agenda for this Week

I SPARQL (2 lectures)

I Semantic Search

I Ontology Engineering

I Pattern-based Ontology Design

I Semantic Web Applications, Closing


Outline

1 SPARQL Protocol and RDF Query Language

2 SPARQL Protocol


Outline


2 SPARQL Protocol


Semantic Web Layer Cake


Goals of this lecture

I Understanding basic and advanced queries using SPARQL

I Gain knowledge about how to query data sources


SPARQL

I W3C Recommendation 15 January 2008I http://www.w3.org/TR/rdf-sparql-query/

I Standard query language for RDFI Native RDF knowledge basesI knowledge bases viewed as RDF via middleware

I Language for querying for graph patternsI Includes unions, conjunctions and optional patternsI No support for inserts or updates

I Supports extensible testing for values and constraints


http://www.w3.org/TR/rdf-sparql-query/

SPARQL 1.1

I SPARQL 1.1 (W3C Recommendation 21 March 2013)

I http://www.w3.org/TR/sparql11-query/I SPARQL 1.1 Query - Adds support for aggregates, subqueries, projected

expressions, and negation to the SPARQL query language.

I SPARQL 1.1 Update - Defines an update language for RDF graphs.

I SPARQL 1.1 Protocol - Defines an abstract interface and HTTP bindings for aprotocol to issue SPARQL Query and SPARQL Update statements against aSPARQL endpoint.

I SPARQL 1.1 Service Description - Defines a vocabulary and discoverymechanism for describing the capabilities of a SPARQL endpoint.

I SPARQL 1.1 Uniform HTTP Protocol for Managing RDF Graphs - Describes theuse of the HTTP protocol for managing named RDF graphs on an HTTP server.

I SPARQL 1.1 Entailment Regimes - Defines conditions under which SPARQLqueries can be used with entailment regimes such as RDF, RDF Schema, OWL,or RIF.

I SPARQL 1.1 Property Paths - Defines a more succinct way to write parts ofbasic graph patterns and also extend matching of triple pattern to arbitrarylength paths.


http://www.w3.org/TR/sparql11-query/

SPARQL Query Types

I SELECTI returns the set of variables bound in a query pattern match

I CONSTRUCTI returns an RDF graph constructed by substituting variables in

a set of triple templates

I DESCRIBEI returns an RDF graph that describes the resources found

I ASKI returns whether a query pattern matches any triples or not

(true / false query)


SPARQL SELECT Query

PREFIX . . .

SELECT . . .

FROM . . .

WHERE { . . . }

schemas used in the query

values to be returned

identify source data to query

triple patterns and otherconditions tomatch the graph


SPARQL ASK Query – Example

Query: Is the river Amazon longer than the river Nile?

PREFIX prop : <h t t p : / / d b p e d i a . org / p r o p e r t y />ASK{<h t t p : / / d b p e d i a . org / r e s o u r c e / Amazon River> prop : l e n g t h ? amazon .<h t t p : / / d b p e d i a . org / r e s o u r c e / N i l e> prop : l e n g t h ? n i l e .

FILTER (? amazon > ? n i l e ) .}

Answer: true


SPARQL CONSTRUCT Query – Example

CONSTRUCT query is used to build an RDF graph.

PREFIX ex : <h t t p : / / example . org / schema/>PREFIX r d f : <h t t p : / /www. w3 . org /1999/02/22− r d f−syntax−ns#>CONSTRUCT{

? p e r s o n r d f : t y p e ex : Adu l t .}WHERE{

? p e r s o n ex : age ? ageFILTER (? age > 17)

}

Result is an RDF graph.


SPARQL DESCRIBE Query – Example

DESCRIBE query is used to provide further information about anRDF resource

DESCRIBE <h t t p : / / d b p e d i a . org / r e s o u r c e / Amazon River>

Result is an extensive description of the resource “Amazon River”.Here is just an excerpt:

@ p r e f i x r d f : <h t t p : / /www. w3 . org /1999/02/22− r d f−syntax−ns#> .@ p r e f i x d b p e d i a : <h t t p : / / d b p e d i a . org / r e s o u r c e /> .@ p r e f i x dbpedia−owl : <h t t p : / / d b p e d i a . org / o n t o l o g y/> .

d b p e d i a : Amazon River r d f : t y p e dbpedia−owl : N a t u r a l P l a c e ,dbpedia−owl : P l a c e .

. . .


Basic SPARQL Patterns

I Triple PatternI Similar to an RDF Triple

I subject, predicate, object

I Any component can be a query variableI Any combination of variables in the query is allowed

I Matching patterns in the WHERE clauseI Matching conjunction of triple patternsI Matching a triple pattern to a graph

I Finding bindings between variables and RDF Terms

I Underneath use of reasonersI Inferring triples originally not present in the knowledge base


SPARQL Example

PREFIX f o a f : <h t t p : / / xmlns . com/ f o a f /0.1/>SELECT ?name ? pageWHERE {

? p e r s o n f o a f : page ? page .? p e r s o n f o a f : name ?name

}

?person

?name

?page

foaf:name

foaf:page


Query Example

Data:

@ p r e f i x f o a f : <h t t p : / / xmlns . com/ f o a f /0.1/ > .: a f o a f : name ‘ ‘ S t e f f e n Staab ’ ’ .: a f o a f : homepage <h t t p : / /www. uni−k o b l e n z . de /˜ staab> .: b f o a f : name ‘ ‘ Gerd Groener ’ ’ .: b f o a f : homepage <h t t p : / /www. uni−k o b l e n z . de /˜ g r o e n e r> .

Query:


? p e r s o n f o a f : homepage ? page .? p e r s o n f o a f : name ?name }

Query Result:

name page“Steffen Staab” <http://www.uni-koblenz.de/~staab>

“Gerd Groener” <http://www.uni-koblenz.de/~groener>


<http://www.uni-koblenz.de/~staab>

<http://www.uni-koblenz.de/~groener>

Querying for Blank Nodes

Data:

@ p r e f i x f o a f : <h t t p : / / xmlns . com/ f o a f /0.1/ > .: a f o a f : name ‘ ‘ S t e f f e n Staab ’ ’ .: a f o a f : homepage <h t t p : / /www. uni−k o b l e n z . de /˜ staab> .: b f o a f : name ‘ ‘ Gerd Groener ’ ’ .: b f o a f : homepage <h t t p : / /www. uni−k o b l e n z . de /˜ g r o e n e r> .

Query:

PREFIX f o a f : <h t t p : / / xmlns . com/ f o a f /0.1/>SELECT ? p e r s o n ?name ? pageWHERE {

? p e r s o n f o a f : homepage ? page .? p e r s o n f o a f : name ?name }

Query Result:

person name page_:a “Steffen Staab” <http://www.uni-koblenz.de/~staab>

_:b “Gerd Groener” <http://www.uni-koblenz.de/~groener>




Filters

I Further constrain graph patterns

I Applied to the whole group of patterns

I FILTER clause:

I Support for AND and OR logic operatorsI Extensive applications for testing literalsI Support for numerical operationsI Support for math equality operators for literals (<,=, >)I Use of regular expressionsI support for data types defined in XSL (e.g., comparision of

dates, time)I possible comparison of resources (equal, not equal)I even possible user extensions


FILTER – Value Constraints

Data:

@ p r e f i x dc : <h t t p : / / p u r l . o rg / dc / e l e m e n t s /1.1/> .@ p r e f i x ex : <h t t p : / / example . org / book/> .@ p r e f i x ns : <h t t p : / / example . org / ns#> .ex : book1 dc : t i t l e ‘ ‘SPARQL T u t o r i a l ’ ’ .ex : book1 ns : p r i c e 42 .ex : book2 dc : t i t l e ‘ ‘ The Semant ic Web ’ ’ .ex : book2 ns : p r i c e 23 .

Query:

PREFIX dc : <h t t p : / / p u r l . o rg / dc / e l e m e n t s /1.1/>PREFIX ns : <h t t p : / / example . org / ns#>SELECT ? t i t l e ? p r i c eWHERE { ? x ns : p r i c e ? p r i c e .

FILTER ? p r i c e < 30 .? x dc : t i t l e ? t i t l e }

Query Result:

title price“The Semantic Web” 23


Scope of Filters

I Filters are applied to the whole group of patterns where theyappear.

{ ? x f o a f : name ?name .? x f o a f : homepage ? page .FILTER r e g e x (? name , ‘ ‘ S t e f f e n ’ ’ ) }

{ ? x f o a f : name ?name .FILTER r e g e x (? name , ‘ ‘ S t e f f e n ’ ’ ) .? x f o a f : homepage ? page }

{ FILTER r e g e x (? name , ‘ ‘ S t e f f e n ’ ’ ) .? x f o a f : name ?name .? x f o a f : homepage ? page }

I These patters are equivalent — have the same solution.


FILTER – Regular Expressions

Data:

@ p r e f i x f o a f : <h t t p : / / xmlns . com/ f o a f /0.1/> .: a f o a f : name ‘ ‘ S t e f f e n Staab ’ ’ .: a f o a f : homepage <h t t p : / /www. uni−k o b l e n z . de /˜ staab> .: b f o a f : name ‘ ‘ Gerd Groener ’ ’ .: b f o a f : homepage <h t t p : / /www. uni−k o b l e n z . de /˜ g r o e n e r> .

Query:


? p e r s o n f o a f : homepage ? page .? p e r s o n f o a f : name ?name .FILTER r e g e x (? name , ‘ ‘ S t e f f e n ’ ’ )}

Query Result:




FILTER – Regular Expressions

Data:

@ p r e f i x f o a f : <h t t p : / / xmlns . com/ f o a f /0.1/> .: a f o a f : name ‘ ‘ S t e f f e n Staab ’ ’ .: a f o a f : homepage <h t t p : / /www. uni−k o b l e n z . de /˜ staab> .: b f o a f : name ‘ ‘ Gerd Groener ’ ’ .: b f o a f : homepage <h t t p : / /www. uni−k o b l e n z . de /˜ g r o e n e r> .

Query:


? p e r s o n f o a f : homepage ? page .? p e r s o n f o a f : name ?name .FILTER r e g e x (? name , ‘ ‘ i ’ ’ , ‘ ‘ g r o e n e r ’ ’ )}

Query Result: case insensitive

name page“Gerd Groener” <http://www.uni-koblenz.de/~groener>



Optional Patterns

I include optional triple patterns to match

I optional is a pattern itself — can include further constraints

SELECTWHERE {

. . .OPTIONAL { . . . }

}

I OPTIONAL is left-associative (i.e., operators are groupedfrom left to right)pattern OPTIONAL {pattern } OPTIONAL { pattern }is the same as{ pattern OPTIONAL { pattern } } OPTIONAL { pattern }


Query Example

Data:

@ p r e f i x f o a f : <h t t p : / / xmlns . com/ f o a f /0.1/> .: a f o a f : name ‘ ‘ S t e f f e n Staab ’ ’ .: a f o a f : homepage <h t t p : / /www. uni−k o b l e n z . de /˜ staab> .: b f o a f : name ‘ ‘ Gerd Groener ’ ’ .: b f o a f : mbox <g r o e n e r @ u n i−k o b l e n z . de> .

Query:


? p e r s o n f o a f : name ?name .? p e r s o n f o a f : homepage ? page .}Query Result:




Query Example — OPTIONAL

Data:


Query:


? p e r s o n f o a f : name ?name .OPTIONAL ? p e r s o n f o a f : homepage ? page .}Query Result:


“Gerd Groener”



Union of Graph Pattern

UNION

I combining alternative graph patterns

I if more than one of the alternatives matches, all the possiblepattern solutions are included in result

SELECTWHERE {

{ p a t t e r n }UNION{ p a t t e r n }

}


Query Example — UNION

Data:

@ p r e f i x dc10 : <h t t p : / / p u r l . o rg / dc / e l e m e n t s /1.0/> .@ p r e f i x dc11 : <h t t p : / / p u r l . o rg / dc / e l e m e n t s /1.1/> .book1 dc10 : t i t l e ‘ ‘SPARQL T u t o r i a l ’ ’ .book1 dc10 : c r e a t o r ‘ ‘ A l i c e ’ ’ .book2 dc11 : t i t l e ‘ ‘ The Semant ic Web’ ’ .book2 dc11 : c r e a t o r ‘ ‘ Robert ’ ’ .

Query:

PREFIX dc10 : <h t t p : / / p u r l . o rg / dc / e l e m e n t s /1.0/>PREFIX dc11 : <h t t p : / / p u r l . o rg / dc / e l e m e n t s /1.1/>SELECT ? t i t l eWHERE { { ? x dc10 : t i t l e ? t i t l e }

UNION{ ? x dc11 : t i t l e ? t i t l e } }

Query Result: title“SPARQL Tutorial”“The Semantic Web”


Modification of the Result Set

Result of SPARQL query can be further modified

I ORDER BYI sort results alphabetically / numerically by specific variable

I LIMITI Limit number of returned results (only top n results)

I OFFSETI Skip n top results and return the rest

These expressions can be combined in a query.


Sequencing and Limiting Results

Query:


? p e r s o n f o a f : homepage ? page .? p e r s o n f o a f : name ?name

}ORDER BY ?nameLIMIT 20OFFSET 10


Bound Variables

I one of the FILTER expressions

I supports testing if a variable in a query can be bound to an instancein the knowledge base

I mostly used for negation as failure

PREFIX f o a f : < h t t p : / / xmlns . com/ f o a f /0.1/>SELECT ?nameWHERE {

? p e r s o n f o a f : name ?name .OPTIONAL { ? p e r s o n f o a f : knows ? x . }FILTER ( ! bound (? x ) )

}


Bound Variables – Example

Data:


Query:


? p e r s o n f o a f : name ?name .OPTIONAL { ? p e r s o n f o a f : homepage ? page .}FILTER ( bound (? page ) )

}Query Result:




Tricky Negation

Find people who do not know Steffen.First attempt:

PREFIX f o a f : < h t t p : / / xmlns . com/ f o a f /0.1/>SELECT ?nameWHERE {

? p e r s o n f o a f : name ?name .? p e r s o n f o a f : knows ? x .FILTER ( ? x != ‘ ‘ S t e f f e n ’ ’ ) }

Data:... we know that ...

‘ ‘ Paul ’ ’ f o a f : knows ‘ ‘ S t e f f e n ’ ’‘ ‘ Paul ’ ’ f o a f : knows ‘ ‘ S e r g e j ’ ’

... so “Paul” is still a valid answer (do you know why?)

... and we do not want this!


Negation with bound

Find people who do not know Steffen.

I now the correct way using bound expression and optional graphpattern

PREFIX f o a f : h t t p : / / xmlns . com/ f o a f / 0 . 1 /SELECT ?nameWHERE {

? p e r s o n f o a f : name ?name .OPTIONAL { ? p e r s o n f o a f : knows ? x .

FILTER ( ? x = ‘ ‘ S t e f f e n ’ ’ ) }FILTER ( ! bound (? x ) )

}


Other SPARQL Filter Expressions

Testing if a bounded variable is a blank node.

annotation

:_

Alan Smith

dc:creator

foaf:given

foaf:family


Other SPARQL Filter Expressions (2)

I isBlank: Testing if a bounded variable is a blank node.

SELECT ? g i v e n ? f a m i l yWHERE { ? a n n o t a t i o n dc : c r e a t o r ? c .

OPTIONAL {? c f o a f : g i v e n ? g i v e n .? c f o a f : f a m i l y ? f a m i l y } .

FILTER i s B l a n k (? c ) }

I lang: Accessing the language of a literal

SELECT ?name ?mboxWHERE { ? x f o a f : name ?name .

? x f o a f : mbox ?mbox .FILTER ( l a n g (? name ) = ‘ ‘DE’ ’ ) }



Testing if a bounded variable is a literal (not a resource).

:_

“Gerd”

<[email protected]>

foaf:name

foaf:mbox



I isLiteral: Testing if a bounded variable is a literal (not a resource)


? x f o a f : mbox ?mbox .FILTER i s L i t e r a l (? mbox ) }

I str: Converting resource URI to string for regular expression matching


? x f o a f : mbox ?mbox .FILTER r e g e x ( s t r (? mbox ) , ‘ ‘ @uni−k o b l e n z . de ’ ’ ) }


Equal Terms and Same Terms

I check if two terms are equal or if they describe the same entity

term1 = term2 orsameTerm ( term1 , term2 )

I returns true if

I terms are of the same type (URI, literal, blank node)I two terms represent URIs are equivalentI two terms represent literals are equivalentI two terms are bound by the same blank node

I same entity can have even different URIs, but connected withowl:sameAs


Equal Terms

Find people who have the same email address, but use different names

@ p r e f i x f o a f : <h t t p : / / xmlns . com/ f o a f /0.1/> .: a f o a f : name ‘ ‘ A l i c e ’ ’ .: a f o a f : mbox <m a i l t o : a l i c e @ w o r k . example> .: b f o a f : name ‘ ‘Ms A . ’ ’ .: b f o a f : mbox <m a i l t o : a l i c e @ w o r k . example> .

PREFIX f o a f : <h t t p : / / xmlns . com/ f o a f /0.1/>SELECT ?name1 ?name2WHERE {

? x f o a f : name ?name1 .? x f o a f : mbox ?mbox1 .? y f o a f : name ?name2 .? y f o a f : mbox ?mbox2 .FILTER ( sameTerm (? mbox1 , ?mbox2 ) && ?name1 != ?name2 ) }


User-defined Functions

FILTER enables using user-defined expressions

PREFIX aGeo : <h t t p : / / example . org / geo#>SELECT ? n e i g h b o r WHERE {

? a aGeo : placeName ‘ ‘ Koblenz ’ ’ .? a aGeo : l o c a t i o n ? axLoc .? a aGeo : l o c a t i o n ? ayLoc .?b aGeo : placeName ? n e i g h b o r .?b aGeo : l o c a t i o n ? bxLoc .?b aGeo : l o c a t i o n ? byLoc .FILTER

( aGeo : d i s t a n c e (? axLoc , ? ayLoc , ? bxLoc , ? byLoc ) < 5 )}

Definition of user function geometric distance between two points described by (x, y)coordinates:

xsd:double aGeo:distance (numeric x1, numeric y1, numeric x2, numeric y2)


Querying for Inferred Knowledge

I SPARQL does not have specific constructs for accessing inferred knowledge

I Underlying knowledge base is responsible for supportinginference, e.g.,

I Class hierarchyI Property hierarchyI Transitive or symmetric propertiesI OWL restrictionsI Defining classes by unions and/or intersections

I Different knowledge bases can offer different level of support

I Same knowledge in different knowledge bases may returndifferent results for the same query, depending on supportedentailment


Query Example

Alice Bob

Clare

daughterOf

sonOf

ancestorOf

ancestorOf

ancestorOf

ancestorOf = owl:transitiveProperty ∧ union(inverse(daughterOf), inverse(sonOf))

Find ancestors of Alice:

Query:

SELECT ? xWHERE { ? x a n c e s t o r O f A l i c e }


CONSTRUCT Queries

I Special type of query to construct a new RDF graph from the existingknowledge base

PREFIX

CONSTRUCT{

. . . graph p a t t e r n . . .

. . . d e f i n i t i o n o f t r i p l e s . . .}

WHERE{

c o n s t r a i n t t r i p l e p a t t e r n s ,f i l t e r s , e t c .

}


Constructing Graphs

Data:

@ p r e f i x f o a f :<h t t p : / / xmlns . com/ f o a f /0.1/> .

: a f o a f : g ivenname ” A l i c e ” .: a f o a f : f a m i l y n a m e ” Hacker ” .: b f o a f : f i r s t n a m e ”Bob” .: b f o a f : surname ” Hacker ” .

Result:

@ p r e f i x v c a r d : <h t t p : / /www. w3 . org /2001/ vcard−r d f /3.0#>

: v1 v c a r d :N : x .: x v c a r d : givenName

” A l i c e ” .: x v c a r d : familyName

” Hacker ” .: v2 v c a r d :N : z .: z v c a r d : givenName ”Bob” .

: z v c a r d : familyName” Hacker ” .

Query:

PREFIX f o a f :<h t t p : / / xmlns . com/ f o a f /0.1/>

PREFIX v c a r d : <h t t p : / /www. w3 . org /2001/ vcard−r d f /3.0#>

CONSTRUCT{? x v c a r d :N : v .

: v v c a r d : givenName ?gname .: v v c a r d : familyName ? fname

}WHERE{{ ? x f o a f : f i r s t n a m e ?gname }

UNION{ ? x f o a f : g ivenname ?gname } .{ ? x f o a f : surname ? fname }

UNION{ ? x f o a f : f a m i l y n a m e ? fname }}


ASK Queries

I True / false queries — check if given set of triple patterns hasat least one match in the knowledge base

I Does not include ORDER BY, LIMIT or OFFSET

@ p r e f i x f o a f : <h t t p : / / xmlns . com/ f o a f /0.1/> .: a f o a f : name ” A l i c e ” .: a f o a f : homepage <h t t p : / / work . example . org / a l i c e /> .: b f o a f : name ”Bob” .: b f o a f : mbox <m a i l t o : bob@work . example>

Query:

PREFIX f o a f : <h t t p : / / xmlns . com/ f o a f /0.1/>ASK { ? x f o a f : name ” A l i c e ” .

? x f o a f : mbox ? y }

Answer: NO


DESCRIBE Queries

I Return a graph that includes description of specific resourcesI Results of DESCRIBE queries reveal meta-information not

returned by standard SELECT queriesI Type of bounded resourcesI Types of relationships used in query pattern

I Exact description of resources is determined by the queryservice

I No common standard of descriptionI Can even include information about related resources


DESCRIBE Query Example

PREFIX e n t : <h t t p : / / org . example . com/ employees#>DESCRIBE ? xWHERE { ? x e n t : e m p l o y e e I d ”1234” }

Result:

@ p r e f i x f o a f : <h t t p : / / xmlns . com/ f o a f /0.1/> .@ p r e f i x v c a r d : <h t t p : / /www. w3 . org /2001/ vcard−r d f /3.0> .@ p r e f i x exOrg : <h t t p : / / org . example . com/ employees#> .@ p r e f i x r d f : <h t t p : / /www. w3 . org /1999/02/22− r d f−syntax−ns#> .@ p r e f i x owl : <h t t p : / /www. w3 . org /2002/07/ owl#>

: a exOrg : e m p l o y e e I d ”1234” ;f o a f : mbox sha1sum ”ABCD1234” ;v c a r d :N

[ v c a r d : Fami ly ” Smith ” ;v c a r d : Given ” John ” ] .

f o a f : mbox sha1sum r d f : t y p e owl : I n v e r s e F u n c t i o n a l P r o p e r t y


Named Graphs

I RDF data stores may hold multiple RDF graphs:I record information about each graphI queries that involve information from more than one graphI default graph (does not have a name)I multiple named graphs (identified by URI reference)I direct implementation for reification

I Accessing named graphsI FROM

I access knowledge in default graph

I FROM NAMEDI access information from specific named graph


Remember: Ad hoc reification (direct)

→ remember: there are several alternatives for reification in RDF(modeling choices)

Repetition: Reification (statement on a statement):

Example:“Kant” examined “Jonas” in “Introduction to CS” and gave himgrade “1.0”

How can we model this in RDF?


Ad hoc reification (direct)

“Kant” examined “Jonas” in “Introduction to CS” and gave himgrade “1.0”

s:kant/#me s:exam1 s:introCS

1.0

s:jonas/#me

s:examiner

s:examinee

s:grade

s:in


Named Graph for reification

“Kant” examined “Jonas” in “Introduction to CS” and gave himgrade “1.0”

s:JonasGraph

s:kant/#me s:exam1 s:introCS

1.0

s:examiner

s:grade

s:in

s:Stud2Graph


Named Graphs — Example

Data:

# D e f a u l t graph ( h t t p : / / example . org / f r i e n d s )@ p r e f i x dc : <h t t p : / / p u r l . o rg / dc / e l e m e n t s /1.1/> .<h t t p : / / example . org /bob> dc : p u b l i s h e r ‘ ‘ Bob ’ ’ .<h t t p : / / example . org / a l i c e > dc : p u b l i s h e r ‘ ‘ A l i c e ’ ’ .

# Bob ’ s Graph : h t t p : / / example . org /bob@ p r e f i x f o a f : <h t t p : / / xmlns . com/ f o a f /0.1/> .

: a f o a f : name ‘ ‘ Bob ’ ’ .: a f o a f : mbox <m a i l t o : bob@oldcorp . example . org> .

# A l i c e ’ s Graph : h t t p : / / example . org / a l i c e@ p r e f i x f o a f : <h t t p : / / xmlns . com/ f o a f /0.1/> .

: a f o a f : name ‘ ‘ A l i c e ’ ’ .: a f o a f : mbox <m a i l t o : a l i c e @ w o r k . example . org> .

Query:

SELECT . . .FROM NAMED <h t t p : / / example . org / a l i c e >FROM NAMED <h t t p : / / example . org /bob>. . .


Relationships between Named Graphs

# D e f a u l t graph@ p r e f i x f o a f : <h t t p : / / xmlns . com/ f o a f /0.1/> .

: y f o a f : name ‘ ‘ A l i c e ’ ’ x .: y f o a f : mbox <m a i l t o : a l i c e @ w o r k . example . org> .: y f o a f : mbox <m a i l t o : a l i c e @ o l d c o r p . org> .

# Graph : h t t p : / / example . org / a l i c e@ p r e f i x f o a f : <h t t p : / / xmlns . com/ f o a f /0.1/> .

: a f o a f : name ‘ ‘ A l i c e ’ ’ .: a f o a f : mbox <m a i l t o : a l i c e @ w o r k . example . org> .

# Graph : h t t p : / / example . org / a l i c e p r e v@ p r e f i x f o a f : <h t t p : / / xmlns . com/ f o a f /0.1/> .

: a f o a f : name ‘ ‘ A l i c e ’ ’ .: a f o a f : mbox <m a i l t o : a l i c e @ o l d c o r p . org> .


Accessing the Name of Named Graphs

Data:

Query:

Result:

# Graph : h t t p : / / example . org / a l i c e: a f o a f : name ‘ ‘ A l i c e ’ ’ .: a f o a f : mbox <m a i l t o : a l i c e @ w o r k . example . org> .

# Graph : h t t p : / / example . org / a l i c e p r e v: a f o a f : name ‘ ‘ A l i c e ’ ’ .: a f o a f : mbox <m a i l t o : a l i c e @ o l d c o r p . org> .

SELECT ? s r c ?mboxWHERE {

GRAPH ? s r c{ ? x f o a f : name ‘ ‘ A l i c e ’ ’ .

? x f o a f : mbox ?mbox} }

src mboxhttp://example.org/alice mailto:[email protected]

http://example.org/alice_prev mailto:[email protected]


Restricting Access by Graph Name

Data:

# Graph : h t t p : / / example . org / a l i c e: a f o a f : name ‘ ‘ A l i c e ’ ’ .: a f o a f : mbox <m a i l t o : a l i c e @ w o r k . example . org> .

# Graph : h t t p : / / example . org / a l i c e p r e v: a f o a f : name ‘ ‘ A l i c e ’ ’ .: a f o a f : mbox <m a i l t o : a l i c e @ o l d c o r p . org> .

Query:

PREFIX ex : <h t t p : / / example . org/>SELECT ?mboxWHERE {

GRAPH ex : a l i c e{ ? x f o a f : mbox ?mbox }

}

Result: mboxmailto:[email protected]


Outline


2 SPARQL Protocol


semantic web - sparql - uni-koblenz · semantic web sparql gerd gr oner, matthias thimm...

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