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.

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Semantic Web: The Inside Story

  1. 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
  2. 2. Tetherless World Constellation Original Outline (July 2000)
  3. 3. Tetherless World Constellation History >250 Semantic Web talks since 2000
  4. 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. 5. Tetherless World Constellation <mind:Person rdf:id=“Hendler”> <mind:title jobs:Professor> <jobs:placeOfWork> </mind:Person> DOC1 Hendler DOC1 Mind:title Jobs:placeOfWork Web Page http://www… ProfessorJobs:Mind: Jobs: Links in the data
  6. 6. Tetherless World Constellation <mind:Person rdf:id=“Hendler”> owl:sameAs <> 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. 7. Tetherless World Constellation Linking Web Resources
  8. 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. 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. 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. 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. 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. 13. Tetherless World Constellation Linked Data in many sectors 37 billion links
  14. 14. Tetherless World Constellation But is it getting real world acceptance? Facebook: 2011 Oracle: 2012
  15. 15. Tetherless World Constellation The big winner: The Knowledge Graph Google finds embedded metadata on >20% of its crawl – Guha, 2014
  16. 16. Tetherless World Constellation Semantic Web • What is driving the change? –Maturation of Linked Data technologies •Embedded markup – & RDFa •SPARQL endpoints –graph database standard •Lightweight Knowledge –A little semantics goes a long way
  17. 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!
  18. 18. Tetherless World Constellation Semantic Search IEEE Computer, Jan 2010)
  19. 19. Tetherless World Constellation Contenders ca. 2010
  20. 20. Tetherless World Constellation Google 2009
  21. 21. Tetherless World Constellation Google 2012
  22. 22. Tetherless World Constellation Google 2013
  23. 23. Tetherless World Constellation • The hierarchy and details are all available on line –
  24. 24. Tetherless World Constellation • Why the change from learning to human markup enhanced?
  25. 25. © Peter Mika, 2014.
  26. 26. © Peter Mika, 2014.
  27. 27. © Peter Mika, 2014.
  28. 28. Tetherless World Constellation similar story for Facebook 2012: Extending the Social Graph
  29. 29. Tetherless World Constellation Some others
  30. 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. 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. 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. 33. Tetherless World Constellation Be bold!
  34. 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