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

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