Redlink opens the door to the world of semantics by providing simple Restful APIs, SDKs and Plugins for the most common use cases. Existing CMS can thus seamlessly integrate semantic technologies. The slides also shows how MM Asset Management Systems can profit from Semantic Lifting.

1. Semantic Content Management
Techniques and Tools
Talk at MODULE University Vienna
Thomas Kurz
!
2014/02/06
Vienna, Austria

2. Redlink was founded in 2013/03 and is
headquartered in SALZBURG , Austria.
John
Pereira
Aingaran
Pillai
Andrea
Volpini
Rupert
Westenthaler
Jakob
Frank
Sebastian
Schaffert
Sergio
Fernàndez
Semantic Content Management
Thomas
Kurz
David
Riccitelli
02/36

3. Outline
• Why we need Semantics in CMS ?
• How can Semantic Web Technologies help ?
• How Redlink makes the integration much easier ?
!
• Excursus: What about Semantic Media Asset
Management Systems
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4. "We are drowning in information and starved for knowledge."
John Naisbitt
• Content is highly available through the Internet
• Information are distributed over people and systems
• Data is available in various media and technical formats
We need an efficient way for working with huge
amounts of unstructured content
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5. Content Management Systems
• CMS are a single point of entry, providing consistency and the
foundations for collaborative work with content
• CMS provide functionalities to handle large amounts of content:
•
•
•
•
Creation of new content
Editing of existing content
Organisation and management of content
Presentation of content
• Media-neutral data management (separation of layout and content)
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6. Semantic Content Management
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7. State of Play in Content Management
• Current solutions provide efficient ways to manage
content
• Domain-specific requirements, like “multichannel content
distribution” are addressed
• Content can be managed and presented in multi-media
formats
… B UT …
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8. Problems in current Content Management Systems
• Content is only “understandable” by users and not by machines
•
•
Irrelevant search results
Aggregation of relevant content needs to be done manually
!
• Inferring Knowledge from Content
•
Dependencies, relations and inconsistencies among content items
need to be identified and defined manually
!
• Content is strongly connected to presentation
•
works only inside a certain environment
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9. The GOAL
It would be right/wrong
to sell the product to
John Smith.
WISDOM
John Smith is a
potential customer
for your products
+ Insight
KNOWLEDGE
+ Meaning
INFORMATION
John Smith
is a name
+ Context
John Smith
DATA
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10. Slide by Nova Spivack, Radar Networks
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11. How Semantic Web Technologies can help
http://upload.wikimedia.org/wikipedia/commons/f/f3/Semantic_Web_Stack.png
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12. (Open) Linked Data
1. Use URIs as names for things
2. Use HTTP URIs so that people can look up those names.
3. When someone looks up a URI, provide useful information, using
the standards (RDF*, SPARQL)
4. Include links to other URIs. so that they can discover more things.
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13. Semantic Lifting via Natural Language Processing
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14. How should we handle this?
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15. The Redlink Platform
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01/02

16. The Open Platform for Linked Data
http://marmotta.apache.org/
• Read-Write Linked Data
• Triple store with transactions, versioning and reasoning
• SPARQL and LDPath query languages
• Transparent Linked Data Caching
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17. The Toolbox for Semantic Lifting
http://stanbol.apache.org
• Semantic Enhancement process chaining
• Several Natural Language processing facilities
• Multi-language support
• Classification and Sentiment Analysis
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18. The highgly scalable Search Server
http://lucene.apache.org/solr/
• Based on Apache Lucene
• Many language specific processing procedures
• Highly scalable (Solr cloud) and ultra fast
• Highly configurable
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19. DEV.REDLINK.IO
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20. PART II
!
Media Asset Management
Bridging the Semantic Gap

21. Semantic Media Asset Management Systems
• Multimedia Content is enormously growing within the last
decade (Web 2.0)
• Multimedia Content must be prepared for automatic processing
• for multimedia retrieval
• for reuse across platforms, contexts, locations, languages
• Multimedia Content Management Systems heavily rely on high
quality metadata (meaning is hidden
Semantic Gap)
Semantic Web Technologies can bridge the gap
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01/02

22. Where we use Semantics
• Controlled Vocabularies
• Domain specific Thesauri using standard representations
• Reuse of external data
• Create Knowledge by linking
• (Semi-) Automatic Metadata enrichment and classification
• Semantic Search (Facetting, Synonymes, Multilingual)
What do we need to bring
Media Objects in the Web of Data
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01/02

23. Media Fragments
„ … a media-format independent, standard means of addressing
media fragments on the Web using Uniform Resource Identifiers. “
[W3C Recommendation: Media Fragments URI 1.0 (basic)]
!
temporal
t=10,20
spacial
xywh=0,0,20,20
track
track=audio
id
id=chapter2
!
http://www.w3.org/TR/media-frags/
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01/02

24. Media Resource Description
Ontology for Media Resources 1.0
„ … to bridge the different descriptions of media resources, and
provide a core set of descriptive properties.“
[W3C Recommendation: Ontology for Media Resources 1.0]
!
Open Annotation Collaboration
!
!
!
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01/02

25. Semantic Content Management
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26. Hello, my name is Tom!
Last summer I was in Paris in France for vacation.
It was really amazing. I love Paris!
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27. RDFize Tom's statement
Tom
likes
Paris,
France.
-­‐>
Tom
likes
Paris.
-­‐>
(
Tom,
likes,
Paris
)
-­‐>
Paris
is
a
part
of
France.
-­‐>
(
Paris,
partOf,
France
)
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28. RDFize Tom's statement
Tom
likes
Paris,
France.
-­‐>
Tom
likes
Paris.
-­‐>
(
Tom,
likes,
Paris
)
-­‐>
Paris
is
a
part
of
France.
-­‐>
(
Paris,
partOf,
France
)
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29. Link to external resources
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30. But what about this?
Title:! „Me and the big thing“!
Album:! „A vacation in Paris“!
Author:!
„Tom Tester“!
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31. Extract Information
Title:! „Me and the big thing“!
Album:! „A vacation in Paris“!
Author:!
„Tom Tester“!
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32. Link Information
:image!
:hasFragment!
:image#xywh=...!
!
:image#xywh=...!
:subject foaf:Person!
!
:image !
:hasFragment !
:image#xywh=..!
!
:image#xywh=.. !
:subject !
dbpedia:EiffelTower!
(50%)
Title:!
„Me and the big thing“!
Album:! vacation in <http://dbpedia.org/resource/Paris>“!
„A
Author:! „<http://tom-tester.org/me>“
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33. Outlook
http://www.mico-project.eu/
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34. Create new facts by using Contextual Semantics
:image :hasFragment :image#xywh=...!
:image#xywh=... :subject foaf:Person!
:image :author tom:me!
!
:image :hasFragment :image#xywh=..!
!
:image :location dbpedia:Paris!
:image :location geonames:France!
!
:image#xywh=.. :subject dbpedia:EiffelTower!
(+90%)!
!
:image :showsOnTheLeft tom:me (50%)!
:image :showsOnTheRight dbpedia:EiffelTower!
:image :showsOnTheRight dbpedia:VisitorAtraction!
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35. Outlook
http://www.mico-project.eu/
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36. Thanks for your attention!
Any Questions?
thomas.kurz@redlink.co
Semantic Content Management