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The Semantic Web: RPI ITWS Capstone (Fall 2012)

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Rensselaer Polytechnic Institute
Rensselaer Polytechnic Institute

Overview/introduction to the Semantic Web for RPI ITWS Capstone class (Fall 2012)

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ITWS Capstone Lecture: The Semantic Web John S. Erickson, Ph.D. Director, Web Science Operations Tetherless World Constellation RPI
...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... Greg Hughes
...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!
What really matters?
Is this “Semantic Web” for real?
1989...
1989... ““Vague but exciting...” Vague but exciting...”
2001...
2001...
2001...
2011...
2011...
2011...
2011...
2011...
2011...
2011...
Percent of total catalogs (from 192 catalogs) 19 19
Int'l Open Gov't Dataset Search: Percent of total catalogs searching 1,022,787 datasets (from 192 catalogs) from 192 catalogs in 24 languages representing 43 countries and international organizations (Summer 2012) 20 20
2012...
2012...
Semantic Web?
Semantic Web? “Web of meaning”
Semantic Web? “Web of meaning” Make meaningful Make meaningful assertions assertions about things about things on the Web... on the Web... Web of Data
Semantic Web? “Web of meaning” Web of Data Link ideas... Link ideas... Linked Data
Assertions...
...about ideas???
subject subject predicate object object
subject subject predicate object object article article has creator Jim Jim
doi:10.1109/MC.2009.30 http://purl.org/dc/elements/1.1/ creator http://dbpedia.org/resource/James_Hendler http://dbpedia.org/resource/James_Hendler
doi:10.1109/MC.2009.30 http://purl.org/dc/elements/1.1/ creator http://dbpedia.org/resource/James_Hendler http://dbpedia.org/resource/James_Hendler
That's how to describe things...
...but how do we find things?
SPARQL: pattern matching over RDF graphs
http://bit.ly/RumkhW http://bit.ly/RumkhW ?s ?s dbpedia2:blackboard ?blackboard ?blackboard
http://bit.ly/Rumtlp http://bit.ly/Rumtlp ?s ?s dbpedia2:blackboard ?blackboard ?blackboard
http://bit.ly/RumQwu http://bit.ly/RumQwu
http://bit.ly/RumQwu http://bit.ly/RumQwu “There is no such month ?s ?s dbpedia2:blackboard “There is no such month as “Rocktober” as “Rocktober”
http://bit.ly/RumQwu http://bit.ly/RumQwu
http://bit.ly/RumQwu http://bit.ly/RumQwu http://dbpedia.org/resource/Double,_Double,_Boy_in_Trouble http://dbpedia.org/resource/Double,_Double,_Boy_in_Trouble
When in 2009 The Inventor said unto us...
Use URIs as names for things Use URIs as names for things Use HTTP URIs so that people can look up Use HTTP URIs so that people can look up those names (on the Web) those names (on the Web) When someone looks up a URI, return When someone looks up a URI, return useful information, using the standards useful information, using the standards ((RDF*,SPARQL)) RDF*, SPARQL Include links to other URIs, so that they can Include links to other URIs, so that they can discover more things discover more things
Use URIs as names for things Use URIs as names for things Use HTTP URIs so that people can look up Use HTTP URIs so that people can look up those names (on the Web) those names (on the Web) When someone looks up a URI, return When someone looks up a URI, return useful information, using the standards useful information, using the standards ((RDF*,SPARQL)) RDF*, SPARQL Include links to other URIs, so that they can Include links to other URIs, so that they can discover more things discover more things
The Linked Data Cloud The Linked Data Cloud
The Linked Data Cloud The Linked Data Cloud
The Linked Data Cloud The Linked Data Cloud
How does this help us?
Linked Data enables agile data integration and application creation
Mashup: OrgPedia Open Corporate Data Mashup: OrgPedia Open Corporate Data http://tw.rpi.edu/orgpedia/
Mashup: RPI Research Centers Mashup: RPI Research Centers
Mashup: RPI Research Centers Mashup: RPI Research Centers
Mashup: Research Data Mashup: Research Data
Mashup: Research Data Mashup: Research Data
Example: Extending a Sci Publishing Portal Example: Extending a Sci Publishing Portal
Example: Extending a Sci Publishing Portal Example: Extending a Sci Publishing Portal
Idea: Linking Data-driven Apps with “Smart Content” http://inference-web.org/wiki/Semantic_Water_Quality_Portal http://inference-web.org/wiki/Semantic_Water_Quality_Portal
[data integration/data science]
Schematic for Deep Carbon Virtual Observatory and Interoperability Semantic Integrated Discovery interoperability Analytics Global Census, Virtual visualizations and mining Mineral Laboratory, ... Applications Application-level mediation: vocabulary, mapping to science and data terms Semantic Software, Deep Energy/ interoperability Physics/ …. Res/Flux Life Chemistry Applications Tools & Apps Applications Models Semantic query, Q uery, hypothsis and access and inference use of data Semantic mediation: physics, chemistry, mineral, emission data - ChemML, Metadata, Data schema, Emission/ data GVP MINDAT EOS EarthChem Compositions Repositories ... ... ...
...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...
Semantic Web key concepts... RDF, SPARQL, Linked Data, mashups, dataviz, RDFa, microformats, Schema.org
Semantic Web key concepts... advanced ideas... RDF, SPARQL, ontology, inference, Linked Data, reasoning, provenance, mashups, dataviz, machine learning, RDFa, microformats, policy-based systems Schema.org
Semantic Web key concepts... advanced ideas... RDF, SPARQL, ontology, inference, Linked Data, reasoning, provenance, mashups, dataviz, machine learning, RDFa, microformats, policy-based systems Schema.org careers...
????

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The Semantic Web: RPI ITWS Capstone (Fall 2012)

  • 1. ITWS Capstone Lecture: The Semantic Web John S. Erickson, Ph.D. Director, Web Science Operations Tetherless World Constellation RPI
  • 2. ...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... Greg Hughes
  • 3. ...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...
  • 6. Is this “Semantic Web” for real?
  • 8. 1989... ““Vague but exciting...” Vague but exciting...”
  • 19. Percent of total catalogs (from 192 catalogs) 19 19
  • 20. Int'l Open Gov't Dataset Search: Percent of total catalogs searching 1,022,787 datasets (from 192 catalogs) from 192 catalogs in 24 languages representing 43 countries and international organizations (Summer 2012) 20 20
  • 25. Semantic Web? “Web of meaning” Make meaningful Make meaningful assertions assertions about things about things on the Web... on the Web... Web of Data
  • 26. Semantic Web? “Web of meaning” Web of Data Link ideas... Link ideas... Linked Data
  • 29. subject subject predicate object object
  • 30. subject subject predicate object object article article has creator Jim Jim
  • 31. doi:10.1109/MC.2009.30 http://purl.org/dc/elements/1.1/ creator http://dbpedia.org/resource/James_Hendler http://dbpedia.org/resource/James_Hendler
  • 32. doi:10.1109/MC.2009.30 http://purl.org/dc/elements/1.1/ creator http://dbpedia.org/resource/James_Hendler http://dbpedia.org/resource/James_Hendler
  • 33.
  • 34. That's how to describe things...
  • 35. ...but how do we find things?
  • 37. http://bit.ly/RumkhW http://bit.ly/RumkhW ?s ?s dbpedia2:blackboard ?blackboard ?blackboard
  • 38. http://bit.ly/Rumtlp http://bit.ly/Rumtlp ?s ?s dbpedia2:blackboard ?blackboard ?blackboard
  • 39.
  • 41. http://bit.ly/RumQwu http://bit.ly/RumQwu “There is no such month ?s ?s dbpedia2:blackboard “There is no such month as “Rocktober” as “Rocktober”
  • 43. http://bit.ly/RumQwu http://bit.ly/RumQwu http://dbpedia.org/resource/Double,_Double,_Boy_in_Trouble http://dbpedia.org/resource/Double,_Double,_Boy_in_Trouble
  • 44. When in 2009 The Inventor said unto us...
  • 45.
  • 46. Use URIs as names for things Use URIs as names for things Use HTTP URIs so that people can look up Use HTTP URIs so that people can look up those names (on the Web) those names (on the Web) When someone looks up a URI, return When someone looks up a URI, return useful information, using the standards useful information, using the standards ((RDF*,SPARQL)) RDF*, SPARQL Include links to other URIs, so that they can Include links to other URIs, so that they can discover more things discover more things
  • 47. Use URIs as names for things Use URIs as names for things Use HTTP URIs so that people can look up Use HTTP URIs so that people can look up those names (on the Web) those names (on the Web) When someone looks up a URI, return When someone looks up a URI, return useful information, using the standards useful information, using the standards ((RDF*,SPARQL)) RDF*, SPARQL Include links to other URIs, so that they can Include links to other URIs, so that they can discover more things discover more things
  • 48. The Linked Data Cloud The Linked Data Cloud
  • 49. The Linked Data Cloud The Linked Data Cloud
  • 50. The Linked Data Cloud The Linked Data Cloud
  • 51.
  • 52.
  • 53. How does this help us?
  • 54. Linked Data enables agile data integration and application creation
  • 55. Mashup: OrgPedia Open Corporate Data Mashup: OrgPedia Open Corporate Data http://tw.rpi.edu/orgpedia/
  • 56. Mashup: RPI Research Centers Mashup: RPI Research Centers
  • 57. Mashup: RPI Research Centers Mashup: RPI Research Centers
  • 60. Example: Extending a Sci Publishing Portal Example: Extending a Sci Publishing Portal
  • 61. Example: Extending a Sci Publishing Portal Example: Extending a Sci Publishing Portal
  • 62.
  • 63.
  • 64. Idea: Linking Data-driven Apps with “Smart Content” http://inference-web.org/wiki/Semantic_Water_Quality_Portal http://inference-web.org/wiki/Semantic_Water_Quality_Portal
  • 66. Schematic for Deep Carbon Virtual Observatory and Interoperability Semantic Integrated Discovery interoperability Analytics Global Census, Virtual visualizations and mining Mineral Laboratory, ... Applications Application-level mediation: vocabulary, mapping to science and data terms Semantic Software, Deep Energy/ interoperability Physics/ …. Res/Flux Life Chemistry Applications Tools & Apps Applications Models Semantic query, Q uery, hypothsis and access and inference use of data Semantic mediation: physics, chemistry, mineral, emission data - ChemML, Metadata, Data schema, Emission/ data GVP MINDAT EOS EarthChem Compositions Repositories ... ... ...
  • 67. ...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...
  • 68. Semantic Web key concepts... RDF, SPARQL, Linked Data, mashups, dataviz, RDFa, microformats, Schema.org
  • 69. Semantic Web key concepts... advanced ideas... RDF, SPARQL, ontology, inference, Linked Data, reasoning, provenance, mashups, dataviz, machine learning, RDFa, microformats, policy-based systems Schema.org
  • 70. Semantic Web key concepts... advanced ideas... RDF, SPARQL, ontology, inference, Linked Data, reasoning, provenance, mashups, dataviz, machine learning, RDFa, microformats, policy-based systems Schema.org careers...
  • 71.
  • 72.
  • 73.
  • 74.
  • 75.
  • 76.
  • 77.
  • 78.
  • 79. ????