ITWS Capstone (RPI, Fall 2013)

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...

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...

4. Boil the ocean!

5. What really matters?

6. Is this “Semantic Web” for real?

7. 1989...

8. ““Vague but exciting...”
Vague but exciting...”
1989...

9. 2001...

10. 2001...

11. 2001...

12. Today...

13. Today...

14. Today...

15. Today...

16. Today...

17. Today...

18. Today...

19. Today...

20. Percent of total catalogs
(from 192 catalogs)
20
20

21. Percent of total catalogs
(from 192 catalogs)
Int'l Open Gov't Dataset Search:
searching 1,022,787 datasets
from 192 catalogs
in 24 languages
representing 43 countries
and international organizations
(Summer 2012)
21
21

25. Today...

26. 2012...

27. Semantic Web?

28. Semantic Web?
“Web of meaning”

29. Semantic Web?
“Web of meaning”
Web of Data
Make meaningful
Make meaningful
assertions
assertions
about things
about things
on the Web...
on the Web...

30. Semantic Web?
“Web of meaning”
Web of Data
Link ideas...
Link ideas...
Linked Data

31. Assertions...

32. ...about ideas???

33. subject
subject
predicate
object
object

34. subject
subject
predicate
object
object
““article”
article”
“has creator”
““Jim”
Jim”

35. 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

36. 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

38. That's how to describe things...

39. ...but how do we find things?

40. SPARQL:
pattern matching
over RDF graphs

41. SPARQL:
pattern matching
over RDF graphs
““SPARQL Protocol
SPARQL Protocol
and
and
Query Language...”
Query Language...”

42. http://bit.ly/RumkhW
http://bit.ly/RumkhW
?s
?s
dbpedia2:blackboard
?blackboard
?blackboard

43. http://bit.ly/Rumtlp
http://bit.ly/Rumtlp
?s
?s
dbpedia2:blackboard
?blackboard
?blackboard

45. http://bit.ly/RumQwu
http://bit.ly/RumQwu

46. http://bit.ly/RumQwu
http://bit.ly/RumQwu
?s
?s
dbpedia2:blackboard
“There is no such month
“There is no such month
as “Rocktober”
as “Rocktober”

47. http://bit.ly/RumQwu
http://bit.ly/RumQwu

48. 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

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

51. 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

52. 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

53. The Linked Data Cloud
The Linked Data Cloud

54. The Linked Data Cloud
The Linked Data Cloud

55. The Linked Data Cloud
The Linked Data Cloud

58. How does this
help us?

59. Linked Data
enables agile
data integration
and
application creation

60. Mashup: OrgPedia Open Corporate Data
Mashup: OrgPedia Open Corporate Data
http://tw.rpi.edu/orgpedia/

61. Mashup: RPI Research Centers
Mashup: RPI Research Centers

62. Mashup: RPI Research Centers
Mashup: RPI Research Centers

63. Mashup: Research Data
Mashup: Research Data

64. Linked Data Publication: HHS Health Data
Linked Data Publication: HHS Health Data

65. Linked Data Publication: HHS Health Data
Linked Data Publication: HHS Health Data

66. Linked Data Publication: HHS Health Data
Linked Data Publication: HHS Health Data

67. Linked Data Publication: HHS Health Data
Linked Data Publication: HHS Health Data

68. Linked Data Publication: HHS Health Data
Linked Data Publication: HHS Health Data

69. Example: Extending a Sci Publishing Portal
Example: Extending a Sci Publishing Portal

72. 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

73. [data integration/data science]

74. Schematic for Deep Carbon Virtual Observatory and Interoperability
Integrated
Applications
Discovery
visualizations
Semantic
interoperability
Analytics
and mining
Global Census, Virtual
Mineral Laboratory, ...
Application-level mediation: vocabulary,
mapping to science and data terms
Software,
Tools & Apps
Deep Energy/
Life
Applications
Semantic
interoperability
Physics/
Chemistry
Models
Semantic query,
hypothsis and
inference
….
Res/Flux
Applications
Query,
access and
use of data
Semantic mediation: physics, chemistry, mineral, emission data - ChemML,
Data
Repositories
GVP
MINDAT
EOS
EarthChem
Metadata,
schema,
data
... ... ...
Emission/
Compositions

75. [data integration/data science]

76. ...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...

77. Semantic Web
key concepts...
RDF, SPARQL,
Linked Data,
mashups, dataviz,
RDFa, microformats,
Schema.org

78. Semantic Web
key concepts...
advanced ideas...
RDF, SPARQL,
Linked Data,
mashups, dataviz,
RDFa, microformats,
Schema.org
ontology, inference,
reasoning, provenance,
machine learning,
policy-based systems

79. Semantic Web
key concepts...
advanced ideas...
RDF, SPARQL,
Linked Data,
mashups, dataviz,
RDFa, microformats,
Schema.org
ontology, inference,
reasoning, provenance,
machine learning,
policy-based systems
careers...

88. ????