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.

1. Tetherless World Constellation
Semantic Web:
The Inside Story
Jim Hendler
@jahendler
Tetherless World Professor of Computer, Web and Cognitive Science
Director, Rensselaer Institute for Data Exploration and Applications
Rensselaer Polytechnic Institute
http://www.cs.rpi.edu/~hendler

2. Tetherless World Constellation
Original Outline (July 2000)

3. Tetherless World Constellation
History
>250 Semantic Web talks since 2000

4. Tetherless World Constellation
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!

5. Tetherless World Constellation
<mind:Person rdf:id=“Hendler”>
<mind:title jobs:Professor>
<jobs:placeOfWork http://www.cs.rpi.edu>
</mind:Person>
DOC1
Hendler
DOC1 Mind:title
Jobs:placeOfWork Web Page
http://www…
ProfessorJobs:Mind:
Jobs:
Links in the data

6. Tetherless World Constellation
<mind:Person rdf:id=“Hendler”>
owl:sameAs
<http://dbpedia.org/page/James_Hendler>
DOC2
Hendler
Mind:title
Jobs:placeOfWork Web Page
http://www…
Jobs:Professor
Asserting Links in the data
Dbpedia:Hendler
Owl:sameAs
Dbpedia:ComputerScientist
Dbpedia:occupation

7. Tetherless World Constellation
Linking Web Resources
Sindice.com

8. 8NCARAI, Apr 2002
Ontologies can help
Catalog/
ID
General
Logical
constraints
Terms/
glossary
Thesauri
“narrower
term”
relation
Formal
is-a
Frames
(properties)
Informal
is-a
Formal
instance
Value
Restrs.
Disjointness,
Inverse, part-
of…
TAXONOMY ONTOLOGY
(McGuinness, 99)

9. 9NCARAI, Apr 2002
Ontologies can help
Catalog/
ID
General
Logical
constraints
Terms/
glossary
Thesauri
“narrower
term”
relation
Formal
is-a
Frames
(properties)
Informal
is-a
Formal
instance
Value
Restrs.
Disjointness,
Inverse, part-
of…
TAXONOMY ONTOLOGY
(McGuinness, 99)
But is this the right view?

10. 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

11. 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

12. 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.

13. Tetherless World Constellation
Linked Data in many sectors
Linkeddata.org 37 billion links

14. Tetherless World Constellation
But is it getting real world acceptance?
Facebook: 2011 Oracle: 2012

15. Tetherless World Constellation
The big winner: The Knowledge Graph
Google finds embedded metadata on >20% of its crawl – Guha, 2014

16. Tetherless World Constellation
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

17. Tetherless World Constellation
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

18. Tetherless World Constellation
Semantic Search
IEEE Computer, Jan 2010)

19. Tetherless World Constellation
Contenders ca. 2010

20. Tetherless World Constellation
Google 2009

21. Tetherless World Constellation
Google 2012

22. Tetherless World Constellation
Google 2013

23. Tetherless World Constellation
• The schema.org hierarchy and details
are all available on line
–https://schema.org/docs/full.html

24. Tetherless World Constellation
• Why the change from learning to
human markup enhanced?

25. © Peter Mika, 2014.

26. © Peter Mika, 2014.

27. © Peter Mika, 2014.

28. Tetherless World Constellation
similar story for Facebook
2012: Extending the Social Graph

29. Tetherless World Constellation
Some others

30. Tetherless World Constellation
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 vocabularies
No network effect without links

31. Tetherless World Constellation
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!

32. Tetherless World Constellation
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

33. Tetherless World Constellation
Be bold!

34. Tetherless World Constellation
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