semantic cms using the redlink platform by thomas kurz
DESCRIPTION
Originally shared on: http://www.slideshare.net/thkurz1 Redlink (http://redlink.co) provides simple Restful APIs, SDKs and Plugins for the most common use cases. Existing CMS can thus seamlessly integrate semantic technologies. The slides presented at the MODULE University in Vienna this February 2014 also shows how Digital Asset Management Systems can take advantage of Semantic Enrichment.TRANSCRIPT
Talk at MODULE University Vienna Thomas Kurz
!2014/02/06
Vienna, Austria
Semantic Content Management Techniques and Tools
Redlink was founded in 2013/03 and is headquartered in , Austria.SALZBURG
John Pereira
Aingaran Pillai
Andrea Volpini
Sebastian Schaffert
Rupert Westenthaler
Jakob Frank
Thomas Kurz
Sergio Fernàndez
David Riccitelli
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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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"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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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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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 U T …
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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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The GOAL
DATA
INFORMATION
KNOWLEDGE
WISDOM
+ Context
+ Meaning
+ Insight
John Smith
John Smith is a name
John Smith is a potential customer for your products
It would be right/wrong to sell the product to
John Smith.
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Slide by Nova Spivack, Radar Networks
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How Semantic Web Technologies can help
http://upload.wikimedia.org/wikipedia/commons/f/f3/Semantic_Web_Stack.png
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(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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Semantic Lifting via Natural Language Processing
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How should we handle this?
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The Redlink Platform
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• Read-Write Linked Data
• Triple store with transactions, versioning and reasoning
• SPARQL and LDPath query languages
• Transparent Linked Data Caching
The Open Platform for Linked Data
http://marmotta.apache.org/
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• Semantic Enhancement process chaining
• Several Natural Language processing facilities
• Multi-language support
• Classification and Sentiment Analysis
http://stanbol.apache.org
The Toolbox for Semantic Lifting
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• Based on Apache Lucene
• Many language specific processing procedures
• Highly scalable (Solr cloud) and ultra fast
• Highly configurable
http://lucene.apache.org/solr/
The highgly scalable Search Server
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DEV.REDLINK.IO
PART II !
Media Asset Management Bridging the Semantic Gap
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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)
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Semantic Web Technologies can bridge the gap
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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)
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What do we need to bring Media Objects in the Web of Data
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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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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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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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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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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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Link to external resources
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But what about this?
Title:! „Me and the big thing“!Album:! „A vacation in Paris“!Author:!„Tom Tester“!
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Extract Information
Title:! „Me and the big thing“!Album:! „A vacation in Paris“!Author:!„Tom Tester“!
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Link Information
Title:!„Me and the big thing“!Album:!„A vacation in <http://dbpedia.org/resource/Paris>“!Author:! „<http://tom-tester.org/me>“
:image!:hasFragment!:image#xywh=...!!:image#xywh=...!:subject foaf:Person!!:image !:hasFragment !:image#xywh=..!!:image#xywh=.. !:subject !dbpedia:EiffelTower!(50%)
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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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Thanks for your attention! Any Questions?