The document discusses how semantic web technologies can help media companies better structure and utilize their content. It describes challenges media companies face in keeping up with changing platforms and audience needs. Semantic structuring of content through metadata and linked data principles can improve content production, distribution, consumption and monetization. This allows content to be treated and analyzed as data, enhancing discoverability, reuse and generating new revenue opportunities for media companies.

1. Michael S. Dunn
Semantic Web Media Summit
#semanticmedia | @glemak
New York – 09/14/11

2. Semantic Web & Media
• Problem: State of Media & Content
– The Media Industry has been in catch-up mode
since the web started
– How can we get ahead of the curve and maximize
the utilization and value of our content?
• Solution: Structuring of Content
– Improve Production | Distribution
– Enhance Consumption | Monetization

3. Semantic Web & Media
• The Constant Transitional State of Media
– Traditional/Original: Shifted to the Web
– Now: Social | Mobile | Local | Aggregation
– Tomorrow: Expect More Demand
– Focus: From Reactive to Proactive
– Timing: Now or Sooner

4. Semantic Web & Media
• Why Foster a Sense of Urgency
– Velocity of Content Requests are Increasing
• Proliferation of Devices | Inbound Access
• Don’t Ignore IPv6
– Markets are Continuously Changing
– Audience Requirements are Shifting
• Real-Time | Niche | Thematic | Contextual

5. Semantic Web & Media
• Hearst as an Example
– Private | Diverse | Decentralized
– Creating Content for Multiple Industries
– TV | Magazines | Newspapers
– Cable | B2B | Marketing | Web Only
– Short Text | Long Form
– Videos | Photos | Slideshows | Audio

6. Semantic Web & Media
• Technology Assumptions
– Existing Content Management Systems
• Content exists in Silos
• Mostly Single Use Content
• Both Centralized & Diverse
• Simple Processes Required
– Limited Journalists | Editors | Creators
• Inability to Grow Staff to meet Demand

7. Semantic Web & Media
• Technology Assumptions
– Workflow changes are Complex
– A Technology Stack Perspective
• Shift Focus from Commodity to Innovation
• Resources focused on Revenue Opportunities

8. Semantic Web & Media
• Return on Investment for Content
– What Markets exist for our Content?
– Have we already “paid” for this content?
• By creating it ourselves
• By licensing it from others
• Via a related or partner entity
– Analytics | Metrics Must Exist
• For Granular Content Elements
• Not just Pages Published

9. Semantic Web & Media
SEARCH
> SEO > CPM
CONTEXT
CONTENT ADVERTISING
SENTIMENT

10. Semantic Web & Media
• No Longer Just About Context of Content
– Context of Audience is a Priority
– Getting the Right Content
– To the Right “Identity”
– Via the Right Mechanism
– At the Right Time
– All Via Bucketed Personalization

11. Semantic Web & Media
• Goal: Ability to Treat Content like Data
– Organize it Better
– Describe it Better
– Discover it Better
– Analyze it Better
– Expose it Better
– Repurpose it Better

12. Semantic Web & Media
• Content as Data
– Automated Metadata
– Semi-Automated via Selection Process
– Systemic via Devices | Tools
– Content Optimization
• Cleansing | Normalizing
• Allow Self Describing
• Make it Harvestable

13. Semantic Web & Media
• Content on the Web Assumptions
– Google doesn’t trust Metadata
– Aggregators Ignore Layout Preferences
– SEO is a Constantly Changing Game
– Audience | Traffic Drivers
• 40% Brand | Marketing
• 30% Search
• 30% Social

14. Semantic Web & Media
• What is the Semantic Web?
– Descriptive Markup Techniques for Content
– Links Associated with Content
– Links Between Content Entities
– Rich Metadata about Content
– Meant to Foster Machine Readability

15. Semantic Web & Media
• Semantics of Semantic Web
– Do Not Get Overwhelmed by the Lexicon
– Linked Data | Web 3.0
– Ontology | Vocabulary | Taxonomy
– Triples | Turtle | OWL | Sparql
– rdf | rdfa | microdata | microformats

16. Semantic Web & Media
• Why Media Industry should be interested in the
Semantic Web
– Create Efficiencies During Content Creation
– Better Understand Content Already Available
– Insure Discoverability of Content
– Take Advantage of Opportunities

17. Semantic Web & Media
• Structured Content Landscape
– Community Driven Standards
– RDFa
• W3C
• IPTC - rnews
• Facebook – Opengraph
– Microformats
– Linked Open Data

18. Linked Open Data

19. Semantic Web & Media
• Structured Content Landscape
– Microdata (html5)
• Schema.org
• Google Rich Snippets
• Focused Primarily on Search
• Vendor Driven - Community Critiqued

20. Semantic Web & Media
• Structuring Content Creates
– Deeper Entity Extraction
– Generates Richer Metadata
– Generates Better Tags & Links
– Associates Related Content
– Generates Reusable Structured Content
– Improve Workflows
• Reporting | Research | Editorial | Production

21. Semantic Web & Media
• Why is Structured Content More Relevant
– Accessibility
– Interoperability
– Allows Value Assessment
– Meaningful Relationships
– Searchable
– Discover Sentiment
– Maximize Reusability

22. Semantic Web & Media
• Value Your Content
– Utilize Open Standards
– Insure Data Portability
– Aim for Broadest Solution
– Avoid Vendor Lock-In
– Own Your Structured Content
• Consider Drupal
– 2 Way Semantic CMS

23. Semantic Web & Media
• Goals to Consider: Productivity
– Reduce Time to Market
– Increase Insight
– Improve Consistency
– Create a “Toolkit” for “Owned” Content

24. Semantic Web & Media
• Goals to Consider: Content
– Increase Usage
– Lower Cost to Produce
– Improve Discoverability
– Leverage 2 Way Structured Content

25. Semantic Web & Media
• Goals to Consider: Audience
– Improve User Experience
– Increase Levels of User Engagement
– Allow Better Personalization & Targeting
– Enable a Content API

26. Semantic Web & Media
• Goals to Consider: Revenue
– Enhance Existing Streams
– Enable Net New Opportunities
– Integrate with Semantic Ecosystem
• Advertising
• Search
• Social
• Aggregation

27. Semantic Web & Media (Framework)
Search Social
(SEO/SEM) Networks
Contextual Audience (SMM)
Advertising Web
Data
Networks Browser Mobile+ Partners Exchange Services
(SAAS)
html api xml microformats rss OWL RDFa
tagging node specific
Layout Bus
UX sentiment
machine-readable NLP contextualization
Analysis metadata
CRM
entity
Semantic Bus relationships
extraction findability syndication attributes
Ontologies
Vocabularies
CMS Categories DAM
<@glemak>

28. Semantic System Architecture (Inform)
Author 
‣ Content Creation Services
‣ Semantic Data Repository
‣ Semantic Data Analysis
‣ Content Selection Algorithms
‣ Webservices
‣ Content Distribution Services
 Audience
Content Selection Algorithms
‣ Semantic Analysis of Content
‣ Algorithms > Editorial Criteria
‣ Maximize Relevancy/Relatedness
‣ Maximize Click-Through
‣ Maximize Monetization

29. Semantic Web & Media
• Utilization by Media Companies
– Web Content Management
• Automated Topic Pages
• Text Mining | Entity Extraction
• Deep Categorization
• Related Content | Media | Tagging
– Social Media
– Business Intelligence
– Recommendations

30. Semantic Web & Media
• Focus on Semantic Web
– Academia | Researchers | Standards |
Entrepreneurs
– Need Enterprise Engagement
• How to Start…
– Lead with Revenue Enhancement Opportunities
– Show How to Solve Business Problems
– Show How to Measure Results

31. http://about.me/glemak