STC Summit 2010: Semantic Web and Content Strategy
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STC Summit 2010: Semantic Web and Content Strategy

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This is a slightly longer version of the presentation, given at STC's Technical Communications Summit '10 in Dallas, May 5, 2010.

This is a slightly longer version of the presentation, given at STC's Technical Communications Summit '10 in Dallas, May 5, 2010.

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  • This is a longer version of my presentation, given at STC's Technical Communications Summit '10 in Dallas, May 5, 2010. The slightly shorter version can be found here: http://www.slideshare.net/rlovinger/theres-no-semantic-web-without-content-and-data
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STC Summit 2010: Semantic Web and Content Strategy STC Summit 2010: Semantic Web and Content Strategy Presentation Transcript

  • THERE’S NO SEMANTIC WEB WITHOUT CONTENT AND DATA MAY 5, 2010 TECHNICAL COMMUNICATION SUMMIT ’10 RACHEL LOVINGER @RLOVINGER © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • “Language is magic, and computers are still dumb." - Aaron Straup Cope (flickr.com) 2 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • BLACKBERRY © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • BLACKBERRY © 2010 Razorfish. All rights reserved. Confidential and proprietary. Photo by enrique dans
  • BLACKBERRY © 2010 Razorfish. All rights reserved. Confidential and proprietary. Photo by Rob MacEwen
  • AGENDA ‣ What is the semantic web? ‣ The key ingredients ‣ How it’s being used now ‣ What it means for Content Strategy 6 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • WHAT IS THE SEMANTIC WEB? © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • TRANSLATE THAT INTO COMPUTER-ESE The underlying strategy of the Semantic Web is to create data and websites that are “machine-readable.” If machines comprehend the meaning of data and content, they can: ‣ manipulate data in more meaningful ways ‣ provide precisely the information that the user wants 8 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • IS THERE A STARBUCKS NEARBY? 9 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • A FRENCH RESTAURANT? 10 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • GIFT FOR YOUR SUPERHERO NIECE? ? ? ? ? ? ? ? ? 11 © 2010 Razorfish. All rights reserved. Confidential and proprietary. Photo by Brendan Riley
  • FIND A HAIR APPOINTMENT Search for specific criteria: • Highly-rated salon • Near the office • Available time that fits your busy schedule 12 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • SOLVING FOR COMPLEXITY Machines are good at complex things that people do poorly • Computing or recalling long strings of numbers • Comparing large sets of data • Searching through millions of pages or data records for a specific item 13 © 2010 Razorfish. All rights reserved. Confidential and proprietary. Image by Eric Dobbs
  • SOLVING FOR COMPLEXITY People are good at some complex things that machines don’t handle well Equivalence 6:00pm and 18:00 Lumping similar things 6:00pm and 8:23am Splitting different things 6:07:10 and 060710 Semantic systems are designed to capture the logic that will allow them to understand these types of relationships within data and use them to create new facts about the data. 14 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • THE KEY INGREDIENTS © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • HOW DO MACHINES KNOW WHAT DATA MEANS? Identity + Definition + Structure 16 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • IDENTITY + DEFINITION + STRUCTURE 17 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • IDENTITY + DEFINITION + STRUCTURE IDs ‣ Machines need a unique, consistent way to identify a thing or concept. ‣ People can usually tell by context, but a machine needs a unique identifier to be able to make connections or distinctions. Bill Clinton = President Bush President Bush President William Jefferson Clinton (George H. W.) (George W.) 18 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • IDENTITY: STANDARDS Standard identifiers ISBN: International Standard Book Number ISMN: Music ISAN: Audiovisual works 19 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • IDENTITY: OPEN SOURCE MusicBrainz: database of music metadata, licensed by BBC to augment web pages The Police MBID: 9e0e2b01-41db-4008-bd8b-988977d6019a 20 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • IDENTITY + DEFINITION + STRUCTURE 21 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • IDENTITY + DEFINITION + STRUCTURE Ontology Define classifications, properties, relationships, and logic Blackberry1 is a type of Fruit A Fruit is an Edible Thing Blackberry2 is a type of Wireless E-mail Device A Wireless E-mail Device is a Mobile Electronic Device Properties of Edible Things: Seasonal – Yes/No Calories – # Ingredients (optional) – other Edible Things A Mobile Electronic Device can never be an Edible Thing. 22 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • IDENTITY + DEFINITION + STRUCTURE 23 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • IDENTITY + DEFINITION + STRUCTURE Some non-standard ways to express semantics ‣ MicroFormats – uses XHTML & HTML markup to embed meaning in a webpage ‣ hCard for contact information ‣ hCalendar for events <span class="vevent"> <span class="summary">This presentation was given</span> on <span class="dtstart">2010-04-16</span> at the Content Strategy Forum in <span class="location">Paris, France</span>. </span> ‣ Machine Tags – definition added to simple user tagging (“folksonomy”) ‣ flora:tree=coniferous ‣ upcoming:event=81334 24 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • IDENTITY + DEFINITION + STRUCTURE 25 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • IDENTITY + DEFINITION + STRUCTURE 26 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • IDENTITY + DEFINITION + STRUCTURE New Web Standards Developed specifically for expressing metadata and metadata relationships ‣ Dublin Core – an ISO standard defining 15 common metadata elements ‣ RDF – a model for expressing metadata as triples (subject-predicate-object) ‣ OWL – adds semantic meaning ‣ SKOS – expresses structured controlled vocabularies, taxonomies Object Subject 27 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • DUBLIN CORE METADATA INITIATIVE 28 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • DUBLIN CORE A very flexible standard that defines 15 core metadata elements. ‣ contributor – An entity responsible for making contributions to the resource. ‣ coverage – The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant. ‣ creator – An entity primarily responsible for making the resource. ‣ date – A point or period of time associated with an event in the lifecycle of the resource. ‣ description – An account of the resource. ‣ format – The file format, physical medium, or dimensions of the resource. ‣ identifier – An unambiguous reference to the resource within a given context. 29 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • DUBLIN CORE CONTINUED ‣ language – A language of the resource. ‣ publisher – An entity responsible for making the resource available. ‣ relation – A related resource. ‣ rights – Information about rights held in and over the resource. ‣ source – A related resource from which the described resource is derived. ‣ subject – The topic of the resource. ‣ title – A name given to the resource. ‣ type – The nature or genre of the resource. 30 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • RDF – RESOURCE DESCRIPTION FRAMEWORK 31 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • RDF Purpose: To provide a structure (aka framework) for describing identified things (aka resources) Identified? The thing you’re talking about must be identified in a unique way. http://www.foaf.com/Person#RachelLovinger http://www.allmovie.com/Actor#WillSmith Note: URIs (uniform resource identifiers) look like URLs, but might not represent an actual web page. 32 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • RDF Composed of three basic elements ‣ Resources – the things being described ‣ Properties – the relationships between things ‣ Classes – the buckets used to group the things 33 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • RDF The elements are combined to make simple statements in the form of Triples <Subject> <Predicate> <Object> 34 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • RDF The elements are combined to make simple statements in the form of Triples Object Subject 35 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • RDF The elements are combined to make simple statements in the form of Triples <Subject> <Predicate> <Object> Example statement: “Men In Black stars Will Smith” Example triple: <MenInBlack> <hasStar> <WillSmith> 36 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • RDF Information Expressed in Triples <http://www.w3.org/2001/sw/RDFCore/ntriples/> <dc:creator> "Dave Beckett" . <http://www.w3.org/2001/sw/RDFCore/ntriples/> <dc:creator> "Art Barstow" . <http://www.w3.org/2001/sw/RDFCore/ntriples/> <dc:publisher> <http://www.w3.org/> . Can also be expressed as XML <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1/"> <rdf:Description rdf:about="http://www.w3.org/2001/sw/RDFCore/ntriples/"> <dc:creator>Art Barstow</dc:creator> <dc:creator>Dave Beckett</dc:creator> <dc:publisher rdf:resource="http://www.w3.org/"/> </rdf:Description> </rdf:RDF> 37 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • A SAMPLE OF RDF PROPERTIES ‣ type ‣ subClassOf ‣ subPropertyOf ‣ range ‣ domain ‣ label ‣ comment 38 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • RDF PROPERTIES type – indicates that a resource belongs to a certain class <WillSmith> <type> <Actor> This defines which properties will be relevant to Will Smith. 39 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • RDF PROPERTIES subClassOf – a class belongs to a parent class <Actor> <subClassOf> <Person> This means that all members of the Actor class are also members of the Person class. All properties are inherited, and new properties specific to Actor can be added. <WillSmith> <type> <Actor> Implies: <WillSmith> <type> <Person> 40 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • RDF PROPERTIES subPropertyOf – a property has a parent property <hasStar> <subPropertyOf> <hasActor> This means that, if you make a statement using the hasStar property, a more general statement using the hasActor property is also true. <MenInBlack> <hasStar> <WillSmith> Implies: <MenInBlack> <hasActor> <WillSmith> 41 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • RDF PROPERTIES range & domain – the types of resources that use a property <hasStar> <range> <Actor> <hasStar> <domain> <Movie> This means that, if you make a statement using the hasStar property, the system will assume that the subject is a Movie and the object is an Actor. <WillSmith> <hasStar> <MenInBlack> is an untrue statement, but not invalid 42 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • RDF PROPERTIES label – a human-readable name for a resource <http://www.allmovie.com/Actor#WillSmith> <label> <Will Smith> 43 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • RDF PROPERTIES comment – a human-readable description <http://www.pretendwebsite.com/rlovinger-semantic- web.pdf> <comment> <A presentation that Rachel gave at the Technical Communication Summit ‘10> 44 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • RDF: WEB OF TRIPLES EdibleThing Fruit BerryPie Blackberry1 45 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • RDF: WEB OF TRIPLES EdibleThing Fruit BerryPie IngredientOf Blackberry1 abc 123 xyz 46 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • RDF: CONCLUSION Why is RDF uniquely suited to expressing data and data relationships? ‣ More flexible – data relationships can be explored from all angles ‣ More efficient – large scale, data can be read more quickly ‣ not linear like a traditional database ‣ not hierarchical like XML 47 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • OWL – WEB ONTOLOGY LANGUAGE 48 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • 49 © 2010 Razorfish. All rights reserved. Confidential and proprietary. Winnie the Pooh and characters © A. A. Milne,, drawing by Ernest H. Shepard
  • OWL Purpose: To develop ontologies that are compatible with the World Wide Web. Ontologies? Definition and classification of concepts and entities, and the relationships between them. 50 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • OWL Based on the basic elements of RDF; adds more vocabulary for describing properties and classes. Allows the creation of rules that help further explain what things mean. ‣ Relationships between classes ‣ Equality ‣ Richer properties ‣ Class property restrictions 51 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • OWL: RELATIONSHIPS BETWEEN CLASSES ‣ disjointWith – resources belonging to one class cannot belong to the other <Person> <disjointWith> <Country> ‣ complementOf – the members of one class are all the resources that do not belong to the other <InanimateThings> <complementOf> <LivingThings> 52 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • OWL: EQUALITY ‣ sameAs – indicates that two resources actually refer to the same real-world thing or concept <wills> <sameAs> <wismith> ‣ equivalentClass – indicates that two classes have the same set of members <CoopBoardMembers> <equivalentClass> <CoopResidents> 53 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • OWL: RICHER PROPERTIES ‣ Symmetric – a relationship between A and B is also true between B and A <WillSmith> <marriedTo> <JadaPinkettSmith> implies: <JadaPinkettSmith> <marriedTo> <WillSmith> ‣ Transitive – a relationship between A and B and between B and C is also true between A and C <piston> <isPartOf> <engine> <engine> <isPartOf> <automobile> implies: <piston> <isPartOf> <automobile> 54 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • OWL: RICHER PROPERTIES CONTINUED ‣ inverseOf – a relationship of type X between A and B implies a relationship of type Y between B and A <starsIn> <inverseOf> <hasStar> <MenInBlack> <hasStar> <WillSmith> implies: <WillSmith> <starsIn> <MenInBlack> 55 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • OWL: CLASS PROPERTY RESTRICTIONS Define the members of a class based on their properties ‣ allValuesFrom – resources with properties that only have values that meet this criteria ‣ Example: Property: hasParents, allValuesFrom: Human ‣ Resources that meet this criteria can be defined as also being members of the Human class ‣ someValuesFrom – resources with properties that have at least one value that meets criteria ‣ Example: Property: hasGraduated, someValuesFrom: College ‣ Resources that meet this criteria can be defined as being members of the CollegeGraduates class 56 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • OWL: WEB OF TRIPLES PLUS LOGIC EdibleThing Fruit BerryPie IngredientOf Blackberry1 abc 123 xyz Note: Blackberry2 cannot be an ingredient of BerryPie, because it’s not an EdibleThing and all ingredients of EdibleThings must also be EdibleThings 57 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • THIS SEEMS COMPLICATED. WHY DO IT? These capabilities allow systems to express and make sense of first order logic. All men are mortal Socrates is a man Therefore, Socrates is mortal 58 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • OWL: INFERENCING ‣ Create new triples based on existing triples ‣ Deduce new facts based on the stated facts <piston> <isPartOf> <engine> <engine> <isPartOf> <automobile> implies: <piston> <isPartOf> <automobile> 59 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • OWL: THREE FLAVORS ‣ OWL Lite – uses a subset of the capabilities ‣ OWL DL – uses all the capabilities, but some are used in restricted ways ‣ OWL Full – unrestricted use of capabilities; no guarantee that all resulting statements are valid 60 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • SKOS – SIMPLE KNOWLEDGE ORGANIZATION SYSTEM 61 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • SKOS ‣ Also based on RDF ‣ Designed specifically to express information that’s more hierarchical – broader terms, narrower terms, preferred terms and other thesaurus-like relationships ‣ Extendable into OWL, if needed 62 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • LINKED DATA 63 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • LINKED DATA: A DISTRIBUTED APPROACH A Web of Data Image by Richard Cyganiak and Anja Jentzsch 64 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • LINKED DATA: A DISTRIBUTED APPROACH One page per concept ‣ URL is a type of ID ‣ “topic pages” – a powerful tool and reference point ‣ high SEO value ‣ aggregate content ‣ contain related data & IDs 65 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • HOW IT’S BEING USED NOW © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • WALL STREET JOURNAL MOVIE REVIEWS 67 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • ENRICHED SEARCH RESULTS Yahoo! SearchMonkey Google Rich Snippets + 68 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • ENRICHED VANITY SEARCH 69 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • GETGLUE – RATINGS AND RECOMMENDATIONS 70 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • GETGLUE – RATINGS AND RECOMMENDATIONS 71 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • THE NEW YORK TIMES – ALUMNI IN THE NEWS 72 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • BBC MUSIC BETA – ARTISTS PAGES 73 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • BBC PROGRAMME PAGES 74 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • DATA.GOV “The purpose of Data.gov is to increase public access to high value, machine readable datasets generated by the Executive Branch of the Federal Government.” 75 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • FLUVIEW National Flu Activity Map – a widget by CDC.gov 76 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • DATA.GOV.UK 77 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • DATA.GOV.UK APPS Help you find things ‣ A post box ‣ A school ‣ An affordable place to live ‣ A job ‣ A volunteering opportunity ‣ A dentist ‣ A pharmacy ‣ A bike route ‣ A hospital ‣ A parking spot Cyclestreets.net ‣ A care home 78 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • PARKOPEDIA 79 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • DATA.GOV.UK APPS Get information on ‣ How taxes are spent ‣ Renewable energy projects ‣ Technology investments ‣ Planning Alerts ‣ Crime stats ‣ Anti-social behavior in the area ‣ The geological makeup of your area ‣ Hazardous street conditions ‣ Geographical details ‣ Local issues ‣ Local government ‣ Health ‣ Obesity ‣ Real Estate fillthathole.org.uk 80 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • ASBOROMETER 81 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • WHAT IT MEANS FOR CONTENT STRATEGY © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • 83 © 2010 Razorfish. All rights reserved. Confidential and proprietary. Photo by Jon Higgins
  • SEMANTIC CAPABILITIES Content Strategists should get familiar with these new kinds of tools and services ‣ Related Content Services ‣ Advanced Media Monitoring ‣ Semantic Publishing Tools ‣ Semantic Ad Targeting ‣ Rich Data Services ‣ Machine-Assisted Tagging ‣ Semantic SEO 84 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • RELATED CONTENT SERVICES ‣ Enhance existing pages ‣ Identify key concepts ‣ Place assets and information on the page or link to relevant offsite content ‣ Video, images, user- generated reviews, tweets, Wikipedia entries, etc. 85 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • RELATED CONTENT SERVICES Example Services Apture Provides additional contextual information in multimedia pop-ups, drawn from places such as Wikipedia, YouTube and Flickr. Evri Allows readers to browse articles, images, and videos related to the topic of an article or content element, and provides widgets for sidebars, posts and popovers. Headup Provides contextually relevant material from social networks and web services. NewsCred Augments content with related stories from 6000 top news sources, as well as topic pages and license-free photos. Zemanta Suggests related content and pictures that editors can embed in articles or blog posts. 86 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • ADVANCED MEDIA MONITORING ‣ Track Twitter, social networks, blogs, discussion boards, content sites ‣ Track a brand, industry, domain or topic ‣ With semantic capabilities: ‣ more accurate relevance ‣ sentiment analysis ‣ Track ongoing stories and audience reaction 87 © 2010 Razorfish. All rights reserved. Confidential and proprietary. Screenshot © 2010 Phase 2 Technology
  • ADVANCED MEDIA MONITORING Example Services Imooty Tracks keywords and mentions of a brand, using a simple dashboard or by creating alerts, widgets, or RSS feeds. Inbenta Follow the topics that people in your business are following. Lexalytics Scans what’s being said in blogs, tweets and social media to provide sentiment analysis about companies, topics and current events. Tattler Mines news, websites, blogs, multimedia sites, and social media to find mentions of topics or issues of interest to you. 88 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • SEMANTIC PUBLISHING TOOLS ‣ Content management tools that incorporate a wide range of structure and metadata capabilities ‣ Create and publish content encoded with semantic markup and meaningful metadata ‣ Not necessary to understand all the underlying code ‣ Streamlines the publishing process ‣ Makes it faster, easier, and cheaper to bring new content products to market 89 © 2010 Razorfish. All rights reserved. Confidential and proprietary. Screenshot © 2010 Thomson Reuters
  • SEMANTIC PUBLISHING TOOLS Example Services OpenPublish A version of Drupal with OpenCalais machine assisted tagging and RDFa formatting built in. Jiglu Insight Finds hidden relationships to other content you’ve published and automatically creates links. 90 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • SEMANTIC AD TARGETING ‣ Analyzing content pages for message, context, or mood, and inserts relevant ads ‣ Creates highly desirable ad inventory ‣ Audience targeting, without the privacy concerns of behavioral targeting ‣ Brand protection against unfortunate term-matching An example of non-semantic contextual ads 91 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • SEMANTIC AD TARGETING Example Services ad pepper Provides ad placement, lead generation and brand protection through semantic analysis of page content and user behavior. Peer39 Understands the meaning and sentiment of web pages so that ads can be targeted to appropriate audiences, and also protects advertisers from having their campaigns placed on negative or objectionable content. Identifies hot topics on the fly, and quickly adapts to create new “premium” inventory. Proximic Performs real-time content analysis to accurately target ads, builds user profiles for better audience targeting, and includes brand protection measures. 92 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • RICH DATA SERVICES ‣ Enhance content with linked data ‣ Import additional information, assets, services, and user- generated content ‣ Improve SEO ‣ Obtain additional data and content for application development ‣ Data set may already include map to other desirable data and services 93 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • RICH DATA SERVICES Example Services Factual An open data platform providing tools to enable anyone to contribute and use sources of structured data. Freebase An open, semantically enhanced database of information, similar to Wikipedia, but with structured data on millions of topics in dozens of domains. iGlue A community editable database containing images, video, individuals, institutions, and geographic locations. 94 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • MACHINE-ASSISTED TAGGING ‣ Streamlines the process of tagging content by extracting concepts on a page ‣ Suggests a set of consistent tags for each piece of content ‣ Content producer approves or rejects each suggested tag 95 © 2010 Razorfish. All rights reserved. Confidential and proprietary. Screenshot © 2010 Thomson Reuters
  • MACHINE-ASSISTED TAGGING Example Services OpenCalais Automatically tags people, places, companies, facts and events found in the content. TextWise Generates weighted, relevant metadata based on key concepts found in the text of a document or web page. Tagaroo An OpenCalais plug-in for WordPress. 96 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • SEMANTIC SEO ‣ Adds semantic markup to the content, or validates existing markup ‣ Submits it to search engines ‣ Boosts search rankings ‣ Makes pages more accessible for visually impaired users ‣ Displays additional business data, content, or product information directly in search results 97 © 2010 Razorfish. All rights reserved. Confidential and proprietary. Screenshot © 2010 Dapper
  • SEMANTIC SEO Example Services Google Rich Tests webpage markup to ensure that Google’s Rich Snippets feature Snippets can interpret it correctly. Testing Tool Inbenta Assists in the creation of content using the terminology of popular search queries. Semantify Provides automated semantic enhancement of a site without changing (by Dapper) its pages. Search engines see the site with RDFa tagging embedded in the page. 98 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • ADDITIONAL RESOURCES ‣ RDF Primer (http://www.w3.org/TR/REC-rdf-syntax) ‣ OWL / Semantic Web (http://www.w3.org/2004/OWL) ‣ SKOS (http://www.w3.org/2004/02/skos) ‣ Dublin Core (http://dublincore.org) ‣ LinkedData.org – Resources from across the Linked Data community ‣ Sindice (http://sindice.com) – The semantic web index ‣ SchemaWeb (http://www.schemaweb.info) – A directory of RDF schemas ‣ Semantic Universe (http://www.semanticuniverse.com) – Educating the World About Semantic Technologies and Applications) ‣ Semanticweb.org – A wiki for the semantic community ‣ ReadWriteWeb: Semantic Web Archives (http://www.readwriteweb.com/archives/semantic-web/) ‣ Nimble – A Razorfish-Semantic Universe report coming out soon 99 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • CONCLUSION ‣ Content Strategy will still be needed to help implement and use these tools ‣ Related Content Services, Semantic Ad Targeting, Rich Data Services, Semantic SEO, Taxonomy/Ontology/Controlled Vocabularies ‣ Establish business rules ‣ Help configure the tools ‣ Periodically monitor the results ‣ Make adjustments as needed ‣ Advanced Media Monitoring, Semantic Publishing Tools, Machine-Assisted Tagging ‣ Ongoing interaction by insightful, skilled users ‣ CS might be the primary user ‣ CS might train others to get the best results from their use 100 © 2010 Razorfish. All rights reserved. Confidential and proprietary.
  • QUESTIONS? Rachel.Lovinger@razorfish.com Twitter: @rlovinger http://scattergather.razorfish.com Thank you! 101 © 2010 Razorfish. All rights reserved. Confidential and proprietary.