Mike Dunn Presentation
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Transcript of Mike Dunn Presentation
Michael S. Dunn
Semantic Web Media Summit #semanticmedia | @glemak New York – 09/14/11
• 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
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
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
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
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
Semantic Web & Media
• Technology Assumptions
– Workflow changes are Complex
– A Technology Stack Perspective
• Shift Focus from Commodity to Innovation
• Resources focused on Revenue Opportunities
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
Semantic Web & Media
SEARCH
CONTENT ADVERTISING
CONTEXT
> SEO > CPM
SENTIMENT
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
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
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
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
Semantic Web & Media
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
• 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
Semantic Web & Media
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
• Structured Content Landscape
– Community Driven Standards
– RDFa
• W3C
• IPTC - rnews
• Facebook – Opengraph – Microformats
– Linked Open Data
Semantic Web & Media
Linked Open Data
• Structured Content Landscape
– Microdata (html5)
• Schema.org
• Google Rich Snippets
• Focused Primarily on Search
• Vendor Driven - Community Critiqued
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
Semantic Web & Media
• Why is Structured Content More Relevant
– Accessibility
– Interoperability
– Allows Value Assessment
– Meaningful Relationships
– Searchable
– Discover Sentiment
– Maximize Reusability
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
Semantic Web & Media
• Goals to Consider: Productivity
– Reduce Time to Market
– Increase Insight
– Improve Consistency
– Create a “Toolkit” for “Owned” Content
Semantic Web & Media
• Goals to Consider: Content
– Increase Usage
– Lower Cost to Produce
– Improve Discoverability
– Leverage 2 Way Structured Content
Semantic Web & Media
• Goals to Consider: Audience
– Improve User Experience
– Increase Levels of User Engagement
– Allow Better Personalization & Targeting
– Enable a Content API
Semantic Web & Media
• Goals to Consider: Revenue
– Enhance Existing Streams
– Enable Net New Opportunities
– Integrate with Semantic Ecosystem
• Advertising
• Search
• Social
• Aggregation
Semantic Web & Media
Semantic Bus
CMS DAM
CRM
Advertising Networks
Web Services (SAAS)
Browser Mobile+ Partners
xml rss api RDFa
Analysis
Contextual Audience Search
(SEO/SEM)
html
Social Networks
(SMM)
OWL microformats
metadata
entity extraction
contextualization
attributes
relationships
machine-readable
syndication
Ontologies Vocabularies Categories
findability
NLP
Layout Bus node specific
UX sentiment
tagging
Data Exchange
<@glemak>
Semantic Web & Media (Framework)
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
• 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
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
Semantic Web & Media
http://about.me/glemak