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Towards Dynamic and Smart Content 
Theresa Grotendorst 
TEKOM Europe Roadshow Wien 2014 
Semantic Technologies for Adaptiv...
Towards Dynamic and Smart Content 
- The past and the future 
- Content in context - How does a good user experience look ...
The Future is NOW 
Past v.s. 
Future 
Limited screens & devices Unlimited screens & devices 
Content is limited to a speci...
What Web Browser? - The Internet of Things 
Wearables Augmented Reality 
Smart Home 
Smart Devices 
Virtual Reality
What’s good technical documentation? 
It is not only the information provided itself, but rather 
a contextual and user-or...
User Centric Technical Documentation 
„one size fits all“ vs. contextual/tailored content 
targeting an audience vs. targe...
Content in Context 
How does a good user experience look like? 
Scenario: 
Peter and his friend are on a motorbike trip th...
Content in Context 
Providing the right information 
Detailed enough without too much extra information 
Limited set of re...
Content in Context 
Peter searches for "fixing clutch" on Google 
Google finds lot of content containing the letters C-L-U...
Content in Context 
Peter searches for "fixing clutch" on Google 
If Peter is lucky he will find an one-fits-all 
standard...
Content in Context 
Peter searches for "fixing clutch" on Google 
OR a landing page that is published 
dynamically and adj...
Content in Context 
It shows 
- local emergency number 
- a step-by-step instruction on how 
to fix a broken clutch (adjus...
What users want … Implication for Technical Content 
Easily accessible, 
available anytime anywhere 
Highly relevant, 
eas...
What machines want … Implication for Technical Content 
Content that that can 
easily processed by 
machines 
Content that...
Smart Content is… 
structurally & semantically rich 
adaptive & dynamically published
Content Evolution 
Semantic 
meaning 
Highly automated 
Logical 
structure 
Flat text 
Unstructured 
Content 
Consumed 
by...
Content Evolution 
Semantic 
meaning 
Highly automated 
Logical 
structure 
Flat text 
Unstructured 
Content 
Consumed 
by...
Structured Authoring with DITA 
Topic Oriented XML Data Model for Authoring and Publishing 
! 
Core DITA Topic Types: 
– C...
Structured Authoring with DITA 
http://help.adobe.com/en_US/FrameMaker/8.0/help.html?content=Chap22-Structured-Authoring-u...
What’s missing? 
A way for representing knowledge, to add meaning to content 
to go beyond tagging 
parts of the content w...
Using Semantics to enhance content 
Why semantics? 
People understand… Machines don’t.
What is meaning? 
A piece of information is really only defined by 
what it's related to, and how it's related. 
There rea...
Linked Data 
Publishing structured data so that it can be 
interlinked and become more useful. 
This enables data from dif...
http://wikipedia.org/Spain http://wikipedia.org/ 
Madrid 
hyperlink 
Linked Data
http://wikipedia.org/Spain http://wikipedia.org/ 
Madrid 
has capital city 
Linked Data
It’s no new world 
Semantics are already in place..
It’s no new world 
Semantics are already in place..
Linked Open Data 
Creadit: Wikipedia CC BY-SA 3.0
"People can't share knowledge if they don't speak a common language." 
Machines neither. 
Ontologies
Ontologies 
http://wikipedia.org/Spain http://wikipedia.org/ 
Madrid 
has capital city 
Country City 
Tripel 
• The simple...
"People can't share knowledge if they don't speak a common language." 
Machines neither. 
Ontologies
Ontologies 
• Ontologies encode the meaning of the content in a form that 
can be interpreted by machines 
• implicit info...
Ontologies 
Ontology Search LOV (lov.okfn.org/)
From structured Content o Smart Content 
Semantic 
meaning 
Highly automated 
Logical 
structure 
Flat text 
Unstructured ...
From DITA to Linked Data 
The DITA RDF project by Colin Maudry 
More Details: 
Twitter: @CMaudry 
http://purl.org/dita/dit...
From DITA to Linked Data 
Why RDF? 
• RDF is efficient storage and linking mechanism 
• It stores facts about DITA topics,...
DITA RDF Ontology 
by Colin Maudry 
http://bit.ly/DitaRdfLucidChart
Semantic Technologies in Action 
Use Cases 
VW 
Contextual Search for Volkswagen and the Automotive Industry 
Renault 
Sem...
Use Case - VW 
Contextual Search for Volkswagen and the Automotive Industry 
„Whereas previously searches were syntactic, ...
Use Case - Renault 
Semantic Web Technologies in Automotive Repair and Diagnostic 
„The goal being to show that, rather th...
Use Case - Audi 
How Ontologies and Rules Help to Advance Automobile Development 
More Details: http://www.w3.org/2001/sw/...
Semantics in the Content Value Chain 
Content Acquisition 
Content pooling, storage and integration of internal & external...
Keep the conversation going… 
Theresa Grotendorst 
Twitter: @2welten
Nächste SlideShare
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Towards Dynamic and Smart Content - Semantic Technologies for Adaptive Technical Documentation

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"Towards Dynamic and Smart Content - Semantic Technologies for Adaptive Technical Documentation" - TEKOM Roadshow Wien/Vienna 2014

DE:
Die Anforderungen an technische Kommunikation wachsen rasant und stellen den Nutzer und seine individuellen Bedürfnisse zunehmend in den Fokus. So liegt der Wert guter technischer Dokumentation nicht mehr allein in den bereitgestellten Informationen selbst, sondern vielmehr in der Fähigkeit, ein kontextbezogenes und nutzerorientiertes "Hilfe-Erlebnis" zu bieten, welches dynamisch auf die spezifischen Bedürfnisse des Nutzers eingeht. Wie können solche Informationsprodukte in Zukunft aussehen und welche Rolle spielt Semantik dabei? Dieser Vortrag führt in die Grundlagen semantischer Technologien ein und zeigt die Potenziale von intelligenten Inhalten bzw. "Smart Content" für die technische Kommunikation auf.

EN:
The value of technical communication lies no longer just in the technical content itself, but rather in the ability to provide a helpful and desired content experience, responding to the device, location and the personal needs of your customers. What does this complexity mean for technical content, it’s infrastructure, related technologies and processes? How to create adaptive content, which automatically adjusts to different environments and customers needs? In this talk we will discusses a dynamic and personalized content publishing approach based on semantic technologies. This talk will provide you with an understanding of how to support adaptive content using semantic technologies in order to create the best possible content experience - far beyond technical documentation as we know it today.

Veröffentlicht in: Internet
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Towards Dynamic and Smart Content - Semantic Technologies for Adaptive Technical Documentation

  1. 1. Towards Dynamic and Smart Content Theresa Grotendorst TEKOM Europe Roadshow Wien 2014 Semantic Technologies for Adaptive Technical Documentation
  2. 2. Towards Dynamic and Smart Content - The past and the future - Content in context - How does a good user experience look like? - From Structured Content to Smart Content - Using semantics to enhance content - From DITA to Linked Data - Use Cases
  3. 3. The Future is NOW Past v.s. Future Limited screens & devices Unlimited screens & devices Content is limited to a specific purpose Content adapts to context automatically Standardized content experience Personalized and tailored content experience Not scalable, linear content production Dynamically content publishing on-demand Content is only interpretable by humans Content is interpreted and processed by machines
  4. 4. What Web Browser? - The Internet of Things Wearables Augmented Reality Smart Home Smart Devices Virtual Reality
  5. 5. What’s good technical documentation? It is not only the information provided itself, but rather a contextual and user-oriented "help-experience", that adapts dynamically to the specific needs of the user. „People remember experiences, not content.“
  6. 6. User Centric Technical Documentation „one size fits all“ vs. contextual/tailored content targeting an audience vs. targeting a single individual user
  7. 7. Content in Context How does a good user experience look like? Scenario: Peter and his friend are on a motorbike trip through Scotland. It’s 9 pm in the evening when Peter has a Motorcycle breakdown. It’s getting dark..
  8. 8. Content in Context Providing the right information Detailed enough without too much extra information Limited set of relevant links Adaptive to device & context of situation: - Where am I? - What do I need to do? - What information would solve the need? - …
  9. 9. Content in Context Peter searches for "fixing clutch" on Google Google finds lot of content containing the letters C-L-U-T-C-H, but what content is relevant? Clutch, an American rock band Clutch, a women's handbag Motorcycle's Clutch Clutch, what Clutch?
  10. 10. Content in Context Peter searches for "fixing clutch" on Google If Peter is lucky he will find an one-fits-all standardized tutorial/ manual/ technical documentation on how to fix a clutch
  11. 11. Content in Context Peter searches for "fixing clutch" on Google OR a landing page that is published dynamically and adjusts to his needs based on the facts we know: - Search-term („fixing clutch“) - Current location (Highway rest stop) - Time (9 pm) - …
  12. 12. Content in Context It shows - local emergency number - a step-by-step instruction on how to fix a broken clutch (adjustable to Motorcycle Model/Type) - tips on how to secure an accident scene in Scotland - List of next service stations in < 2 kilometers distance - List of nearby hotels & BnB (because it's at night and the stations are probably closed) - Nearby spare part service order form
  13. 13. What users want … Implication for Technical Content Easily accessible, available anytime anywhere Highly relevant, easily consumable Immediately actionable Personalized based on context of situation Always up-to-date and interactive Multichannel, multi-screen publishing Detailed enough without too much extra information Clear & consistent guidance for desired results User context & pattern analysis, content optimization / adaptation Automatically updated, dynamically published
  14. 14. What machines want … Implication for Technical Content Content that that can easily processed by machines Content that that can be interpreted by machines Content that is adaptive to the technology / platform / device Rich metadata, highly structured, granular at the appropriate level Semantic enhancement / encoding the meaning of the content in a form that can be interpreted by machines Responsive content that is dynamically published, not only responsive design
  15. 15. Smart Content is… structurally & semantically rich adaptive & dynamically published
  16. 16. Content Evolution Semantic meaning Highly automated Logical structure Flat text Unstructured Content Consumed by Humans Structured" Content Consumed by Humans Organized & Displayed by Machines Manual Partially Smart Content Consumed by Humans, Organized, Displayed, & Interpreted by Machines High value, Multipurpose Content Medium value, Repurposed Content Lower value, Specific Use Content scalability " of process Richness of markup http://gilbane.com/2009/11/what-is-smart-content/
  17. 17. Content Evolution Semantic meaning Highly automated Logical structure Flat text Unstructured Content Consumed by Humans Structured" Content Consumed by Humans Organized & Displayed by Machines Manual Partially Smart Content Consumed by Humans, Organized, Displayed, & Interpreted by Machines High value, Multipurpose Content Medium value, Repurposed Content Lower value, Specific Use Content scalability " of process Richness of markup http://gilbane.com/2009/11/what-is-smart-content/
  18. 18. Structured Authoring with DITA Topic Oriented XML Data Model for Authoring and Publishing ! Core DITA Topic Types: – Concept – Task – Reference – and more
  19. 19. Structured Authoring with DITA http://help.adobe.com/en_US/FrameMaker/8.0/help.html?content=Chap22-Structured-Authoring-using-DITA_06.html
  20. 20. What’s missing? A way for representing knowledge, to add meaning to content to go beyond tagging parts of the content with random defined tags not interpretable by machines ! ! „Dynamic responsiveness can only be realized when the surrounding infrastructure of the content can ‘understand’ the situational context.“
  21. 21. Using Semantics to enhance content Why semantics? People understand… Machines don’t.
  22. 22. What is meaning? A piece of information is really only defined by what it's related to, and how it's related. There really is little else to meaning. The structure is everything. - Tim Berners-Lee Meaning is all about context, it‘s about how information is related.
  23. 23. Linked Data Publishing structured data so that it can be interlinked and become more useful. This enables data from different sources to be connected and queried.
  24. 24. http://wikipedia.org/Spain http://wikipedia.org/ Madrid hyperlink Linked Data
  25. 25. http://wikipedia.org/Spain http://wikipedia.org/ Madrid has capital city Linked Data
  26. 26. It’s no new world Semantics are already in place..
  27. 27. It’s no new world Semantics are already in place..
  28. 28. Linked Open Data Creadit: Wikipedia CC BY-SA 3.0
  29. 29. "People can't share knowledge if they don't speak a common language." Machines neither. Ontologies
  30. 30. Ontologies http://wikipedia.org/Spain http://wikipedia.org/ Madrid has capital city Country City Tripel • The simplest data structure of an ontology is a triple • All triples follow a very simple scheme • subject (URI) - predicate (URI) - Property / value (URI / literal) • knowledge is modeled as a large number of triplets forming a semantic graph
  31. 31. "People can't share knowledge if they don't speak a common language." Machines neither. Ontologies
  32. 32. Ontologies • Ontologies encode the meaning of the content in a form that can be interpreted by machines • implicit information can be derived automatically from explicit information • enables machine „reasoning“ - deriving facts that are not expressed in the ontology or in knowledge base explicitly. Define… ! • classes • upper and lower classes • Inheritance of information / features • instances • and possible relations between instances • …
  33. 33. Ontologies Ontology Search LOV (lov.okfn.org/)
  34. 34. From structured Content o Smart Content Semantic meaning Highly automated Logical structure Flat text Unstructured Content Consumed by Humans Structured" Content Consumed by Humans Organized & Displayed by Machines Manual Partially Smart Content Consumed by Humans, Organized, Displayed, & Interpreted by Machines High value, Multipurpose Content Medium value, Repurposed Content Lower value, Specific Use Content scalability " of process Richness of markup http://gilbane.com/2009/11/what-is-smart-content/
  35. 35. From DITA to Linked Data The DITA RDF project by Colin Maudry More Details: Twitter: @CMaudry http://purl.org/dita/ditardf-project
  36. 36. From DITA to Linked Data Why RDF? • RDF is efficient storage and linking mechanism • It stores facts about DITA topics, which are used to: – Link internal and external content, create a network of knowledge – Derive other facts (Enables Inferencing) – Provide higher quality search results – Semantic Links create a network of Knowledge ! ! RDF compliments DITA ! Turns it into a Semantically Linked DITA
  37. 37. DITA RDF Ontology by Colin Maudry http://bit.ly/DitaRdfLucidChart
  38. 38. Semantic Technologies in Action Use Cases VW Contextual Search for Volkswagen and the Automotive Industry Renault Semantic Web Technologies in Automotive Repair and Diagnostic Audi How Ontologies and Rules Help to Advance Automobile Development
  39. 39. Use Case - VW Contextual Search for Volkswagen and the Automotive Industry „Whereas previously searches were syntactic, based on keywords and phrases, across unstructured and meaningless content (in the eyes of a search engine), we have moved to a model of semantics where meaning and aggregation can be derived and applied.“ More Details: http://www.w3.org/2001/sw/sweo/public/UseCases/Volkswagen/
  40. 40. Use Case - Renault Semantic Web Technologies in Automotive Repair and Diagnostic „The goal being to show that, rather than having all of the procedures written in manuals as they are today, an engine could compute them on the fly, in a way that minimizes the cost of diagnostic.“ More Details: http://www.w3.org/2001/sw/sweo/public/UseCases/Renault/
  41. 41. Use Case - Audi How Ontologies and Rules Help to Advance Automobile Development More Details: http://www.w3.org/2001/sw/sweo/public/UseCases/Audi/
  42. 42. Semantics in the Content Value Chain Content Acquisition Content pooling, storage and integration of internal & external content sources Content Editing Content enrichment, semantic analysis, adaptation and linking of content Content Distribution Provision of machine-readable / semantic interoperable content and metadata Content Consumption Improved findability & contextualisation of content, dynamic publishing
  43. 43. Keep the conversation going… Theresa Grotendorst Twitter: @2welten

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