releasing relational data to the semantic web

Releasing Relational Data to the Semantic Web

Alex [email protected]

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mailto:[email protected]

mailto:[email protected]

Semantic webRelational data

FederationHREIW

Analytics

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There are things we wish to describe.

We need some way to identify each thing.

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On the web, we identify things with a URI.

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A URI is about "identifying" things, not "locating" things (a URL).

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dbp:Chicago

dbp:The_Blues_Brothers_(film)

dbp: http://dbpedia.org/resource/

dbp:Wrigley_Field

dbp:Chicago_Cubs dbp:Barack_Obama

dbp:Pizza

dbp:Chicago_(band)

Things are more interesting if we relate

them.

Relationships are also described by a URI.

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dbp:Chicago

dbp:The_Blues_Brothers_(film)dbp:Wrigley_Field

dbp:Chicago_Cubsdbp:Barack_Obama

dbp:Pizza

dbp:Chicago_(band)

movie:

film_lo

catio

ndbpo:location

dbp: http://dbpedia.org/resource/dbpo: http://dbpedia.org/ontology/

dbpo:owner

dbpo:residence

Triple

<subject> <predicate> <object>

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dbp:Chicago



dbp:Pizza

dbp:Chicago_(band)

movie:

film_lo

catio

ndbpo:location


dbpo:owner

dbpo:residence

Subject

Predicate

Object

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dbp:Wrigley_Field dbpo:location dbp:Chicago

<subject> <predicate> <object>

resource resource resourceor

value

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dbp:Chicago



dbp:Pizza

dbp:Chicago_(band)

movie:

film_lo

catio

ndbpo:location


dbpo:owner

dbpo:residence

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Congratulations! You now know

RDF.

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If things and relationships can be defined by any URI, how do we know

what we're talking about?

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We need metadata.

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Specifically, we need a vocabulary of common

terms that describe our data.

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A class describes a group of things that

share common properties.

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dbp:Chicago dbp:Saint_Louis

dbp: http://dbpedia.org/resource/ex: http://example.org/ontology/rdf: http://www.w3.org/1999/02/22-rdf-syntax-ns#rdfs: http://www.w3.org/2000/01/rdf-schema#

is a

ex:City

dbp:San_Francisco

is a is a

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rdf:type

ex:City

dbp:San_Francisco

rdf:type rdf:type

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rdf:type

ex:City

dbp:San_Francisco

rdf:type rdf:type

rdfs:Class

rdf:type

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ex:City

ex:Location

rdfs:subClassOf


rdfs:Classrdf:type

rdfs:Classrdf:type

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Classes let us talk about kinds of things. Now we

need some way to describe attributes.

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ex:City

dbp:United_States

dbp:Chicago

rdf:type

ex:founded1837

ex:country

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ex:City

dbp:Chicago

rdf:type

ex:founded1837

rdf:Property

rdf:type

rdfs:domainrdfs:range

xsd:gYear

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Congratulations! You now knowRDF Schema.

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How do we find stuff in this data?

SPARQL

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dbp:Chicagodbp:Wrigley_Fielddbp:Chicago_Cubs

dbpo:location


dbpo:owner

rdf:type

ex:City

rdf:type

ex:Stadiumex:Baseball_Team

rdf:type

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dbpo:locationdbpo:owner

ex:City

rdf:type

ex:Stadium

rdf:type

?owner ?stadium ?city

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ex:City

rdf:type

ex:Stadium

rdf:type


?owner dbpo:owner ?stadium . ?stadium dbpo:location ?city .

?stadium rdf:type ex:Stadium . ?city rdf:type ex:City .

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ex:City

rdf:type

ex:Stadium

rdf:type


?owner dbpo:owner ?stadium . ?stadium dbpo:location ?city .

?stadium rdf:type ex:Stadium . ?city rdf:type ex:City .

SELECT ?owner ?stadium ?cityWHERE { ?owner dbpo:owner ?stadium . ?stadium dbpo:location ?city . ?stadium rdf:type ex:Stadium . ?city rdf:type ex:City .}

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Unions JoinsOuter joinsFilter with criteriaProject expressionsSortDuplicate removalSlice (limit / offset)Aggregates (grouping, etc)Subqueries

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SPARQL


FederationHREIW

Analytics

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Sounds interesting.But my data is in a relational database!

Music Database

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MID First Last Inst_ID

1 Eddie Van Halen 10

2 Yo Yo Ma 20

3 Kenny G 30

Musicians:

IID Instrument Type

10 Guitar String

20 Cello String

30 Saxophone Woodwind

Instruments:

Musician Schema

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music:Instrument

rdfs:domain

music:Musician

rdf:type

rdfs:Class rdf:Property

music:firstName

music:lastName

music:plays

music:instName

music:instType

rdf:type

rdfs:domain

rdfs:domain

rdfs:range

rdfs:domainrdfs:domain

Triples From Tables

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2 Yo Yo Ma 20

3 Kenny G 30

Musicians:

artist:1 rdf:type music:Musicianartist:2 rdf:type music:Musicianartist:3 rdf:type music:Musician

Turn each key into a resource and specify the proper type of each resource:

IID Instrument Type

10 Guitar String

20 Cello String


Instruments:

instrument:10 rdf:type music:Instrumentinstrument:20 rdf:type music:Instrumentinstrument:30 rdf:type music:Instrument

Triples From Tables

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2 Yo Yo Ma 20

3 Kenny G 30

Musicians:

artist:1 music:firstName "Eddie"artist:1 music:lastName "Van Halen"artist:2 music:firstName "Yo Yo"artist:2 music:lastName "Ma"artist:3 music:firstName "Kenny"artist:3 music:lastName "G"

Turn each cell into a triple based on the key, property (mapped per column), and value:

IID Instrument Type

10 Guitar String

20 Cello String


Instruments:

instrument:10 music:instName "Guitar"instrument:10 music:instType "String"instrument:20 music:instName "Cello"instrument:20 music:instType "String"instrument:30 music:instName "Saxophone"instrument:30 music:instType "Woodwind"

Triples From Tables

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2 Yo Yo Ma 20

3 Kenny G 30

Musicians:

artist:1 music:plays instrument:10artist:1 music:plays instrument:20artist:2 music:plays instrument:30

Turn each foreign key reference into a relationship between the foreign and primary resources.

IID Instrument Type

10 Guitar String

20 Cello String


Instruments:

R2RML

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• "Relational to RDF Mapping Language"

• RDB2RDF Working Group at W3C

• ETL "data transformation" use case

• Dynamic "query translation" use case

• SPARQL to SQL

R2RML Triple Mapping

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IID Instrument Type

10 Guitar String

music:Instrumentmusic:instName

music:instType

rdfs:domain

rdfs:domain

Instruments:


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IID Instrument Type

10 Guitar String


music:instType

rdfs:domain

rdfs:domain

Instruments:

Triples Map rr:tableName


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IID Instrument Type

10 Guitar String


music:instType

rdfs:domain

rdfs:domain

Instruments:

Triples Map

Subject Map"http://example.com/music/

Inst-{iid}"

rr:class

rr:tableName


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IID Instrument Type

10 Guitar String


music:instType

rdfs:domain

rdfs:domain

Instruments:

Triples Map

Subject Map"http://example.com/music/

Inst-{iid}"

Predicate Object Map

Predicate Map

Object Map

rr:class

rr:tableName

rr:predicate

rr:column

@prefix rr: <http://www.w3.org/ns/r2rml#> .@prefix music: <http://example.com/music/> .@prefix mapping: <http://example.com/ont/> .

mapping:InstrumentMapping a rr:TriplesMapClass; rr:tableName "Instruments"; rr:subjectMap [ rr:template "http://example.com/music/Inst-{iid}"; rr:class music:Instrument ]; rr:predicateObjectMap [ rr:predicateMap [ rr:predicate music:instName ]; rr:objectMap [ rr:column "instrument" ]; ]; rr:predicateObjectMap [ rr:predicateMap [ rr:predicate music:instType ]; rr:objectMap [ rr:column "type" ]; ];.

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SPARQL translation

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R2RML

SPARQL

SQL Results

Solutions

Database


FederationHREIW

Analytics

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SPARQL Protocol

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• Standard HTTP API for calling a SPARQL processor

• Supported by all major triple stores and query processors

SPARQL Federation

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SELECT ?artist ?song ?buyLinkWHERE { SERVICE <http://listening> { ?listened rdf:type listen:event . ?listened listen:artist ?artist . ?listened listen:song ?song } OPTIONAL { SERVICE <http://amazon> { ?isbn rdf:type amaz:mp3 . ?isbn amaz:artist ?artist . ?isbn amaz:song ?song . ?isbn amaz:link ?buyLink } } }

Call SPARQL endpoint that tracks your listening (like last.fm)

Call Amazon endpoint to get info on where to download the song.

Return Federated data

Service Descriptions

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Federator

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R2RML Endpoint

Web Endpoint

SPARQL Endpoint

Triple Store

SPARQL Endpoint

Federator

Database

Dbpedia

Ontology and service registry

Named graph mapping

• Services can provide named graphs, described in their service description

• Federator lets you create federated named graphs that map to service named graphs

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Data integration

• Performance - data volume from sources is key

• Source capabilities

• Source statistics

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Performance concerns: data volume

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Domain

SELECT ... FILTER (?age >= 24) ...

WHERE Person.age >= 24

Reduction factors:•criteria•minimal projection•aggregation•joins (sometimes)•dup removal

Que

ry

Resu

lts

Performance concerns: federated joins

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Data source capabilities

• SQL support

• Function support

• Function translation

• Inverse functions

• Data type mappings and translations

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Data source statistics

• Table cardinality

• Column selectivity

• Column null density

• Join selectivity

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FederationHREIW

Analytics

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HREIW - HR Analysis

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“Which Marines that speak French and/or French Creole have had at least six months since their last deployment?”

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“How many discharges were the result of the Don’t Ask Don’t Tell

policy per year?”

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“What is the average length of service for soldiers deployed in Afghanistan vs Iraq?”

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Where’s the data?

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Ontologies

HR Domain

Mapping

Sources

HR Standards

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Technologies

HR Domain

Mapping

Sources

HR Standards

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Ontology

development

Analytics

SPARQL Federation

SPARQL to database

Rules

Collaborative Ontologies

Domain ontology

Ontologist Subject Matter Experts

model

discuss

wiki discuss

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diagram

Ontology Visualization

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Federation HREIW

Analytics

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RIF

• Rule Interchange Format, W3C recommendation

• Rule = IF - THEN statement

• Used to derive new triples from existing triples

• Dialects

• Core

• Framework for Logic Dialects (FLD)

• Basic Logic Dialect (BLD)

• Production Rules Dialect (PRD)

• Rex - Revelytix RIF Core implementation

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Dashboards

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Dashboards

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Dashboards

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Enterprise Semantic Web

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• Knoodl - collaborative ontology creation

• OntVis - ontology visualization (OWL)

• Spyder - SPARQL to SQL (RDF, R2RML)

• Federator - SPARQL federation (SPARQL 1.1, SPARQL Federation extensions)

• Rex - entailment with rules (RIF)

• Dashboards - analytics, visualization

More information

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• Revelytix - http://revelytix.com

• Knoodl - http://knoodl.com

• OntVis - http://bit.ly/hLm3sd

• Spyder - http://revelytix.com/content/spyder

• Federator - beta coming soon...

• Rex - beta coming soon...

http://www.revelytix.com/content/spyder

http://www.revelytix.com/content/spyder

releasing relational data to the semantic web

Technology

louis dbp

cubs dbp

location dbp

obama dbp

film dbp

typ dbp

pizza dbp

band dbp