semantic web: the inside story

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In this talk I review some of the early visions of the Semantic Web, some of the different views, and I follow through on a thread of how Semantic Web technology has been adopted in search engines (and other companies). I end with a challenge to the research community to keep pursuing this research, rather than letting industry take over the "low end" and keep new work from flourishing.

TRANSCRIPT

Tetherless World Constellation

Semantic Web:The Inside Story

Jim Hendler@jahendler

Tetherless World Professor of Computer, Web and Cognitive ScienceDirector, Rensselaer Institute for Data Exploration and Applications

Rensselaer Polytechnic Institute

http://www.cs.rpi.edu/~hendler

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Original Outline (July 2000)

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History

>250 Semantic Web talks since 2000

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On the Web -- links are critical!

<a href= URI>

HTML

Web page Any Web Resource

<a href=“http://…”>

RDF

URI URI

URI

RDF is like the web!

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<mind:Person rdf:id=“Hendler”> <mind:title jobs:Professor> <jobs:placeOfWork http://www.cs.rpi.edu></mind:Person>

DOC1

HendlerDOC1 Mind:title

Jobs:placeOfWork Web Pagehttp://www…

ProfessorJobs:Mind:

Jobs:

Links in the data

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<mind:Person rdf:id=“Hendler”> owl:sameAs<http://dbpedia.org/page/James_Hendler>

DOC2

HendlerMind:title

Jobs:placeOfWork Web Pagehttp://www…

Jobs:Professor

Asserting Links in the data

Dbpedia:Hendler

Owl:sameAs

Dbpedia:ComputerScientist

Dbpedia:occupation

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Linking Web Resources

Sindice.com

8NCARAI, Apr 2002

Ontologies can help

Catalog/ID

GeneralLogical

constraints

Terms/glossary

Thesauri“narrower

term”relation

Formalis-a

Frames(properties)

Informalis-a

Formalinstance Value

Restrs.

Disjointness, Inverse, part-

of…

TAXONOMY ONTOLOGY

(McGuinness, 99)

9NCARAI, Apr 2002

Ontologies can help

Catalog/ID

GeneralLogical

constraints

Terms/glossary

Thesauri“narrower

term”relation

Formalis-a

Frames(properties)

Informalis-a

Formalinstance Value

Restrs.

Disjointness, Inverse, part-

of…

TAXONOMY ONTOLOGY

(McGuinness, 99)

But is this the right view?

Ontology: the OWL DL view

• Ontology as Barad-Dur (Sauron's tower):– Extremely powerful!

– Patrolled by Orcs• Let one little hobbit

in, and the whole thing could come crashing down

inconsistency

Decidable Logic basis

ROI: Reasoning over (Enterprise) data

• This "big O" Ontology finds use cases in verticals and enterprises– Where the vocabulary can be controlled– Where finding things in the data is important

• Example– Drug discovery from data

• Model the molecule (site, chemical properties, etc) as faithfully and expressively as possible

• Use "Realization" to categorize data assets against the ontology– Bad or missed answers are money down the drain

ontology: the Linked Data view

• ontology and the tower of Babel– We will build a tower

to reach the sky– We only need a little

ontological agreement

• Who cares if we all speak different languages?

Genesis 11:7 Let us go down, and there confound their language, that they may not understand one another's speech. So the Lord scattered them abroad from thence upon the face of all the earth: and they left off to build the city.

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Linked Data in many sectors

Linkeddata.org 37 billion links

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But is it getting real world acceptance?

Facebook: 2011 Oracle: 2012

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The big winner: The Knowledge Graph

Google finds embedded metadata on >20% of its crawl – Guha, 2014

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Semantic Web

• What is driving the change?– Maturation of Linked Data

technologies•Embedded markup

– Schema.org & RDFa •SPARQL endpoints

– graph database standard•Lightweight Knowledge

– A little semantics goes a long way

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Linked Data + Semantics

• "Linked Data" approach finds its use cases in Web Applications (at Web scales)– A lot of data, a

little semantics– Finding anything

in the mess can be a win!

http://www.cs.rpi.edu/~hendler/LittleSemanticsWeb.html

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Semantic Search

IEEE Computer, Jan 2010)

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Contenders ca. 2010

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Google 2009

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Google 2012

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Google 2013

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• The schema.org hierarchy and details are all available on line

–https://schema.org/docs/full.html

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• Why the change from learning to human markup enhanced?

© Peter Mika, 2014.

© Peter Mika, 2014.

© Peter Mika, 2014.

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similar story for Facebook

2012: Extending the Social Graph

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Some others

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The gap is growing

• Linked-Data-based applications are growing in size, number and importance on the Web– But the “vocabulary” story is still

unclear• Ontology research is turning OWL

into a usable KR standard,– But the linking story is still unclear

No linking without vocabulariesNo network effect without links

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What I think we MUST do

• Bridging the gap between the linked-data and ontology views requires some key research challenges to be addressed– DL (and FOL) are useful formalisms for

KR&R, but do not address the needs of the Web!

– Empirical comparisons are useful in scaling systems, but do not address the needs of an academic community!

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My Challenge to you

• A sufficient formalism for Semantic Web applications must– Provide a model that accounts for linked

data • What is the equivalent of a DB calculus?

– Provide a means for evaluating incomplete reasoners • In practice we must be able to model A-box

effects as formally as T-box technologies

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Be bold!

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Summary

• The Semantic Web, whether as “linked data” or vocabularies in usage is getting significant use.– in many of the largest web players

• But there’s much more work to do– improving semantics in many applications– exploring appropriate business models

• Academic research remains an exciting area– much is extending formalization or faster queries – some big questions still remain

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