ITWS Capstone Lecture:ITWS Capstone Lecture:

The Semantic WebThe Semantic Web

John S. Erickson, Ph.D.John S. Erickson, Ph.D.Director, Web Science OperationsDirector, Web Science Operations

Tetherless World ConstellationTetherless World ConstellationRPIRPI

...the purpose of the lecture is to summarize the Semantic Web

with key concepts and the introduction of a few advanced ideas

that will be useful to these graduating seniors in grad school

or their careers...

...the purpose of the lecture is to summarize the Semantic Web

with key concepts and the introduction of a few advanced ideas

that will be useful to these graduating seniors in grad school

or their careers...

Boil the ocean!Boil the ocean!

What really matters?

Is this “Semantic Web” for real?

1989...1989...

1989...1989...

““Vague but exciting...”Vague but exciting...”““Vague but exciting...”Vague but exciting...”

2001...2001...

2001...2001...

2001...2001...

Today...Today...

Today...Today...

Today...Today...

Today...Today...

Today...Today...

Today...Today...

Today...Today...

Today...Today...

20202020

Percent of total catalogsPercent of total catalogs(from 192 catalogs)(from 192 catalogs)

21212121

Percent of total catalogsPercent of total catalogs(from 192 catalogs)(from 192 catalogs)

Int'l Open Gov't Dataset Search:Int'l Open Gov't Dataset Search:searching searching 1,022,7871,022,787 datasets datasets

from from 192192 catalogs catalogsin in 2424 languages languages

representing representing 4343 countries countries and international organizationsand international organizations

(Summer 2012)(Summer 2012)

Today...Today...

2012...2012...

Semantic Web?Semantic Web?

““Web of meaning”Web of meaning”

Semantic Web?Semantic Web?

““Web of meaning”Web of meaning”

Web of DataWeb of Data

Make meaningfulMake meaningfulassertionsassertions

about thingsabout thingson the Web...on the Web...

Make meaningfulMake meaningfulassertionsassertions

about thingsabout thingson the Web...on the Web...

Semantic Web?Semantic Web?

““Web of meaning”Web of meaning”

Web of DataWeb of Data

Linked DataLinked Data

Link ideas...Link ideas...Link ideas...Link ideas...

Semantic Web?Semantic Web?

Assertions...

...about ideas???

subjectsubjectsubjectsubject objectobjectobjectobjectpredicatepredicate

subjectsubjectsubjectsubject objectobjectobjectobjectpredicatepredicate

““article”article”““article”article” ““has creator”has creator” ““Jim”Jim”““Jim”Jim”

http://dbpedia.org/resource/James_Hendlerhttp://dbpedia.org/resource/James_Hendlerhttp://dbpedia.org/resource/James_Hendlerhttp://dbpedia.org/resource/James_Hendler

doi:10.1109/MC.2009.30doi:10.1109/MC.2009.30

http://purl.org/dc/elements/1.1/http://purl.org/dc/elements/1.1/creatorcreator

http://dbpedia.org/resource/http://dbpedia.org/resource/James_HendlerJames_Hendlerhttp://dbpedia.org/resource/http://dbpedia.org/resource/James_HendlerJames_Hendler

doi:10.1109/MC.2009.30doi:10.1109/MC.2009.30

http://purl.org/dc/elements/1.1/http://purl.org/dc/elements/1.1/creatorcreator

That's how to describe things...

...but how do we find things?

SPARQLSPARQL: : pattern matchingpattern matchingover RDF graphsover RDF graphs

SPARQLSPARQL: : pattern matchingpattern matchingover RDF graphsover RDF graphs

““SPARQL ProtocolSPARQL Protocolandand

Query Language...”Query Language...”

““SPARQL ProtocolSPARQL Protocolandand

Query Language...”Query Language...”

?s?s?s?s ?blackboard?blackboard?blackboard?blackboarddbpedia2:blackboarddbpedia2:blackboard

http://bit.ly/RumkhWhttp://bit.ly/RumkhWhttp://bit.ly/RumkhWhttp://bit.ly/RumkhW

?s?s?s?s ?blackboard?blackboard?blackboard?blackboarddbpedia2:blackboarddbpedia2:blackboard

http://bit.ly/Rumtlphttp://bit.ly/Rumtlphttp://bit.ly/Rumtlphttp://bit.ly/Rumtlp

http://bit.ly/RumQwuhttp://bit.ly/RumQwuhttp://bit.ly/RumQwuhttp://bit.ly/RumQwu

?s?s?s?s ““There is no such monthThere is no such month

as “Rocktober”as “Rocktober”

““There is no such monthThere is no such monthas “Rocktober”as “Rocktober”dbpedia2:blackboarddbpedia2:blackboard

http://bit.ly/RumQwuhttp://bit.ly/RumQwuhttp://bit.ly/RumQwuhttp://bit.ly/RumQwu

http://bit.ly/RumQwuhttp://bit.ly/RumQwuhttp://bit.ly/RumQwuhttp://bit.ly/RumQwu

http://dbpedia.org/resource/Double,_Double,_Boy_in_Troublehttp://dbpedia.org/resource/Double,_Double,_Boy_in_Troublehttp://dbpedia.org/resource/Double,_Double,_Boy_in_Troublehttp://dbpedia.org/resource/Double,_Double,_Boy_in_Trouble

http://bit.ly/RumQwuhttp://bit.ly/RumQwuhttp://bit.ly/RumQwuhttp://bit.ly/RumQwu

When in 2009 When in 2009 The InventorThe Inventor said unto us... said unto us...

Use Use URIsURIs as names for things as names for things

Use Use HTTP URIsHTTP URIs so that people can look up so that people can look up those names (on the Web)those names (on the Web)

When someone looks up a URI, returnWhen someone looks up a URI, returnuseful information, using the standards useful information, using the standards ((RDFRDF*, *, SPARQLSPARQL))

Include Include links to other URIs,links to other URIs, so that they can so that they can discover more thingsdiscover more things

Use Use URIsURIs as names for things as names for things

Use Use HTTP URIsHTTP URIs so that people can look up so that people can look up those names (on the Web)those names (on the Web)

When someone looks up a URI, returnWhen someone looks up a URI, returnuseful information, using the standards useful information, using the standards ((RDFRDF*, *, SPARQLSPARQL))

Include Include links to other URIs,links to other URIs, so that they can so that they can discover more thingsdiscover more things

Use Use URIsURIs as names for things as names for things

Use Use HTTP URIsHTTP URIs so that people can look up so that people can look up those names (on the Web)those names (on the Web)

When someone looks up a URI, returnWhen someone looks up a URI, returnuseful information, using the standards useful information, using the standards ((RDFRDF*, *, SPARQLSPARQL))

Include Include links to other URIs,links to other URIs, so that they can so that they can discover more thingsdiscover more things

Use Use URIsURIs as names for things as names for things

Use Use HTTP URIsHTTP URIs so that people can look up so that people can look up those names (on the Web)those names (on the Web)

When someone looks up a URI, returnWhen someone looks up a URI, returnuseful information, using the standards useful information, using the standards ((RDFRDF*, *, SPARQLSPARQL))

Include Include links to other URIs,links to other URIs, so that they can so that they can discover more thingsdiscover more things

The Linked Data CloudThe Linked Data CloudThe Linked Data CloudThe Linked Data Cloud

The Linked Data CloudThe Linked Data CloudThe Linked Data CloudThe Linked Data Cloud

The Linked Data CloudThe Linked Data CloudThe Linked Data CloudThe Linked Data Cloud

How does thishelp us?

Linked Data enables agile

data integration and

application creation

Mashup: Mashup: OrgPedia Open Corporate DataOrgPedia Open Corporate DataMashup: Mashup: OrgPedia Open Corporate DataOrgPedia Open Corporate Data

http://tw.rpi.edu/orgpedia/http://tw.rpi.edu/orgpedia/

Mashup: Mashup: RPI Research CentersRPI Research CentersMashup: Mashup: RPI Research CentersRPI Research Centers

Mashup: Mashup: RPI Research CentersRPI Research CentersMashup: Mashup: RPI Research CentersRPI Research Centers

Mashup: Mashup: Research DataResearch DataMashup: Mashup: Research DataResearch Data

Linked Data Publication:Linked Data Publication: HHS Health Data HHS Health DataLinked Data Publication:Linked Data Publication: HHS Health Data HHS Health Data

Linked Data Publication:Linked Data Publication: HHS Health Data HHS Health DataLinked Data Publication:Linked Data Publication: HHS Health Data HHS Health Data

Linked Data Publication:Linked Data Publication: HHS Health Data HHS Health DataLinked Data Publication:Linked Data Publication: HHS Health Data HHS Health Data

Linked Data Publication:Linked Data Publication: HHS Health Data HHS Health DataLinked Data Publication:Linked Data Publication: HHS Health Data HHS Health Data

Linked Data Publication:Linked Data Publication: HHS Health Data HHS Health DataLinked Data Publication:Linked Data Publication: HHS Health Data HHS Health Data

Example:Example: Extending a Sci Publishing Portal Extending a Sci Publishing PortalExample:Example: Extending a Sci Publishing Portal Extending a Sci Publishing Portal

Idea: Idea: Linking Data-driven Apps with “Smart Content”Linking Data-driven Apps with “Smart Content”

http://inference-web.org/wiki/Semantic_Water_Quality_Portalhttp://inference-web.org/wiki/Semantic_Water_Quality_Portalhttp://inference-web.org/wiki/Semantic_Water_Quality_Portalhttp://inference-web.org/wiki/Semantic_Water_Quality_Portal

[data integration/data science]

Discovery visualizations

Analytics and mining

Global Census, Virtual Mineral Laboratory, ...

IntegratedApplications

Application-level mediation: vocabulary,mapping to science and data terms

Semanticinteroperability

SemanticinteroperabilitySoftware,

Tools & Apps

DataRepositories

….

Semantic query,hypothsis and

inference

Query,access anduse of data

Metadata,schema,

data... ... ...

Deep Energy/ Life

Applications

Physics/ Chemistry

Models

Res/FluxApplications

GVP MINDAT EOS EarthChem

Semantic mediation: physics, chemistry, mineral, emission data - ChemML,

Schematic for Deep Carbon Virtual Observatory and Interoperability

Emission/ Compositions

[data integration/data science]

...the purpose of the lecture is to summarize the Semantic Web

with key concepts and the introduction of a few advanced ideas

that will be useful to these graduating seniors in grad school

or their careers...

key concepts...

RDF, SPARQL,RDF, SPARQL,Linked Data, Linked Data,

mashups, dataviz,mashups, dataviz,RDFa, microformats,RDFa, microformats,

Schema.orgSchema.org

Semantic Web

key concepts... advanced ideas...

RDF, SPARQL,RDF, SPARQL,Linked Data, Linked Data,

mashups, dataviz,mashups, dataviz,RDFa, microformats,RDFa, microformats,

Schema.orgSchema.org

ontology, inference,ontology, inference,reasoning, provenance,reasoning, provenance,

machine learning,machine learning,policy-based systemspolicy-based systems

Semantic Web

key concepts... advanced ideas...

RDF, SPARQL,RDF, SPARQL,Linked Data, Linked Data,

mashups, dataviz,mashups, dataviz,RDFa, microformats,RDFa, microformats,

Schema.orgSchema.org

ontology, inference,ontology, inference,reasoning, provenance,reasoning, provenance,

machine learning,machine learning,policy-based systemspolicy-based systems

careers...

Semantic Web

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