Successfully reported this slideshow.
Your SlideShare is downloading. ×

NoTube project results. Bringing TV and Web together.

Ad

Project overview and results


1                  New trends in television: social and semantic
© NoTube project consortiu...

Ad

TV on the Web: growing trend




2        New trends in television: social and semantic

Ad

TV on the Web: channel explosion




3          New trends in television: social and semantic

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Upcoming SlideShare
The Birth of Online TV
The Birth of Online TV
Loading in …3
×

Check these out next

1 of 89 Ad
1 of 89 Ad
Advertisement

More Related Content

Viewers also liked (20)

Advertisement

Similar to NoTube project results. Bringing TV and Web together. (20)

More from MODUL Technology GmbH (20)

Advertisement

NoTube project results. Bringing TV and Web together.

  1. 1. Project overview and results 1 New trends in television: social and semantic © NoTube project consortium. For re-use see notice at end.
  2. 2. TV on the Web: growing trend 2 New trends in television: social and semantic
  3. 3. TV on the Web: channel explosion 3 New trends in television: social and semantic
  4. 4. Source: Nielson Three Screen Report, March 2010 4 New trends in television: social and semantic
  5. 5. From „ Mobile Shopping Framework: The role of mobile devices in the shopping process” by Yahoo! and the Nielson company, January 2011 http://advertising.yahoo.com/industry-knowledge/mobile-shopping-insight.html 5 New trends in television: social and semantic
  6. 6. Including the Web in your TV Yahoo! launches ConnectedTV platform for Web- based widgets on TV (e.g. Flickr, YouTube, facebook, twitter) – Jan 2009 6 New trends in television: social and semantic
  7. 7. Augmenting TV with the Web Blinkx BBTV makes video information and its textual transcript clickable, and links to Web sources such as IMDB and Wikipedia www.blinkxbbtv.com Also Mozilla has a project on showing content around videos using HTML5 www.drumbeat.org 7 New trends in television: social and semantic
  8. 8. Some Web-TV solutions today Stand alone boxes such as • TiVo – original DVR, added on-demand video, YouTube, music and photos from the Web • Boxee – STB offering its own store of apps • AppleTV – relaunched as $99 product tied to iTunes content, and iPhone/iPad integration + Hybrid boxes tied to specific IPTV providers + Games consoles (Sony, Microsoft, Nintendo) also adding Internet and video services to TV! 8 New trends in television: social and semantic
  9. 9. Some Web-TV solutions today First TVs with integrated Web and individual app platforms in 2011. Future TVs will be „connected“ as standard. LG SmartTV, pic courtesy http://www.wired.com/gadgetlab/2011/01/lg-smart-tv/ 9 New trends in television: social and semantic
  10. 10. State of the art in TV • TV content shifting to the Web as delivery platform – An explosion in available content at any time • Web content shifting to the TV as augmentation of the TV experience – An explosion in additional content at any time 10 New trends in television: social and semantic
  11. 11. Limitations of today‘s TV • Too much content in one place – How to find what you want to watch? Sort between live TV, TV on demand, archives, video portals and P2P-TV • Too much functionality at any one time – The whole Internet while you watch TV. But what do viewers really want to be able to do additionally (parallel) to watching TV? 11 New trends in television: social and semantic
  12. 12. Social TV • Integrate the TV experience with the so-called Social Web – Who are my friends and what do they watch? – What do my friends like -> maybe I‘d like it too – Where are my friends now -> connect via the shared TV experience • Key goal for social TV – Enhance my TV experience through my friends‘ TV experience 12 New trends in television: social and semantic
  13. 13. Semantic TV • Add formal semantic descriptions for – TV programmes – TV schedules (EPGs) • Link those descriptions to other semantic data on the Web, cf. Linked Data • Two key use cases for semantic TV: – Filtering of TV content -> personalisation, recommendation – Augmentation of TV content with Web data 13 New trends in television: social and semantic
  14. 14. NoTube project • Integrating TV & Web with help of semantics – Open and interlink TV content in a Web fashion with Linked Open Data • Putting the user back in the driving seat – Connect multitude of distributed personal data with explicit semantics • TV is not bound to the device – Computer as TV & vice versa – Mobile device as remote control 14 New trends in television: social and semantic
  15. 15. NoTube partners 15 New trends in television: social and semantic
  16. 16. Bridging Web and TV cultures 16 New trends in television: social and semantic
  17. 17. Rest of this slideset • Technological background (Semantic Web, Linked Data) • Semantic annotations for TV data (semantic TV) • Extracting knowledge from my activities and social graph (social TV) • TV content recommendation (personalized TV) • The further future: finally … interactive TV 17 New trends in television: social and semantic
  18. 18. (1) Semantic Web, Linked Data “If computers can understand the meaning behind the information they can learn what we are interested in and better help us find what we want.”* * Source: http://www.slideshare.net/HatemMahmoud/web-30-the-semantic-web 18 New trends in television: social and semantic
  19. 19. The Semantic Web The vision of what was termed the “Semantic Web“ first came to public attention through an article in Scientific American in May 2001. “The Semantic Web is not a separate Web but an extension of the current one, in which information is given well-defined meaning, better enabling computers and people to work in cooperation.”* * Source: T. Berners-Lee, J. Hendler, O. Lassila; “The SemanticWeb”, Scientific American, 284(5):34–43, May 2001. 19 New trends in television: social and semantic
  20. 20. HTML HTML was too limited for Web documents – it is purely a presentation format. The tags in HTML have no meaning outside how content should be rendered in the browser, and so the meaning of the content must be interpreted by a human, hence excluding any possibility of machine processing. <u>James Bond</u> James Bond MI5 <b>MI5</b><br> Her Majesty's Her Majesty's Secret Secret Service<br> Service Secret HQ<br> Secret HQ <i>007 England</i><br> 007 England 20 New trends in television: social and semantic
  21. 21. XML <name>James Bond</name> <company> James Bond MI5 <shortname>MI5</shortname> Her Majesty's Secret <fullname>Her Majesty's Secret Service Service</fullname> Secret HQ <address><street>Secret HQ</street> 007 England <postcode>007</postcode> <country>England</country> </address> </company> The core idea of XML – Extensible Markup Language – is to provide for definitions of markup which allows self-describing tags, i.e. tags which describe the meaning of the content they mark up rather than its presentation 21 New trends in television: social and semantic
  22. 22. RDF RDF provides a graph structure for making statements about things. Individual things, and not just files, are given an URI identifier. This is where the Semantic Web begins. <flight>Flight AI288 http://my.org/flightAI288 <from>Vienna</from>- :from http://my.org/Vienna <to>Innsbruck</to> :to http://my.org/Innsbruck dep <dep>1.1. 1200</dep> :dep 01-01-2009T12:00 arr <arr>1.1. 1255</arr> :arr 01-01-2009T12:55 price <price>88€</price> :price „88“ </flight> :currency http://my.org/euro from is a child element of flight from is a property of the resource (syntactic structure) http://my.org/flightAI288 22 New trends in television: social and semantic
  23. 23. RDFS RDF Schema begins to formalise the meaning of things spoken about in RDF on the basis of computational logic. RDFS permits simple ontologies (models about concepts and their properties) to be defined, which can be used to conclude new knowledge. http://my.org/Vienna is a http://my.org/City http://my.org/flightAI288 :from http://my.org/Vienna http://my.org/City :to http://my.org/Innsbruck subClass of http://my.org/PopulatedPlace :dep 01-01-2009T12:00 :arr 01-01-2009T12:55 http://my.org/Vienna :price „88“ is a http://my.org/PopulatedPlace :currency http://my.org/euro 23 New trends in television: social and semantic
  24. 24. OWL OWL broadens the possible expressivity of the ontology. This makes richer models of knowledge about things possible, but at the cost of those models being more complex for a computer to process. http://my.org/Vienna isPlaceIn http://my.org/Austria http://my.org/flightAI288 :from http://my.org/Vienna http://my.org/Austria :to http://my.org/Innsbruck isPlaceIn http://my.org/Europe :dep 01-01-2009T12:00 :arr 01-01-2009T12:55 isPlaceIn is a transitive property :price „88“ :currency http://my.org/euro http://my.org/Vienna isPlaceIn http://my.org/Europe 24 New trends in television: social and semantic
  25. 25. SPARQL The final block of the Semantic Web that we will cover in this introduction is SPARQL, the query language for semantic data using the RDF data model (which includes OWL). Is there a flight from Vienna to somewhere in Austria for a price under 100 euros? http://my.org/flightAI288 SELECT ?flight :from http://my.org/Vienna WHERE :to http://my.org/Innsbruck ?flight :from http://my.org/Vienna :dep 01-01-2009T12:00 ?flight :to ?place :arr 01-01-2009T12:55 ?place :isPlaceIn :price „88“ http://my.org/Austria :currency http://my.org/euro ?flight :price ?price ?flight :currency http://my.org/euro FILTER (?price < 100)‫‏‬ 25 New trends in television: social and semantic
  26. 26. Semantic Web principles • Every concept can be identified with URIs • Resources and relationships are typed semantically • Partial information is acceptable • Absolute truth is not necessary • Evolution as a development principle 26 New trends in television: social and semantic
  27. 27. Linked Data principles • Use URIs as names of things • Use HTTP URIs so that people can look up those names • When someone looks up an URI, provide useful information • Include links to other URIs, so that they can discover more things 27 New trends in television: social and semantic
  28. 28. Semantic Web vs Linked Data “In contrast to the full-fledged Semantic Web vision, linked data is mainly about publishing structured data in RDF using URIs rather than focusing on the ontological level or inference. This simplification - just as the Web simplified the established academic approaches of Hypertext systems - lowers the entry barrier for data providers, hence fosters a widespread adoption.” - Reference vs 28 New trends in television: social and semantic
  29. 29. Linked Data cloud 29 New trends in television: social and semantic
  30. 30. Linked Data for music & TV 30 New trends in television: social and semantic
  31. 31. DBPedia: Wikipedia as Linked Data 31 New trends in television: social and semantic
  32. 32. DBPedia Mobile Pictures from revyu.com Try yourself: http://wiki.dbpedia.org/ DBpediaMobile 32 New trends in television: social and semantic
  33. 33. Resources and representations non-information resource http://dbpedia.org/resource/Berlin HTML representation RDF representation .../page/Berlin .../data/Berlin 33 New trends in television: social and semantic
  34. 34. Linking things, not documents http://dbpedia.org/resource/ABBA sameAs http://www.bbc.co.uk/music/artists/d87e52c5- bb8d-4da8-b941-9f4928627dc8#artist 34 New trends in television: social and semantic
  35. 35. Browsing things, not documents http://dbpedia.org/resource/ABBA themeMusicComposer http://dbpedia.org/resource/Knowing_Me%2C_ Knowing_You..._with_Alan_Partridge 35 New trends in television: social and semantic
  36. 36. Asking for things, not documents Which music artists have composed the theme music for a BBC comedy program? 36 New trends in television: social and semantic
  37. 37. (2) Semantic annotation for TV • What can we annotate in TV? – The program schedule – The TV program – TV program segments • How can we annotate TV? – Feature description (low level, analysis based) – Metadata (date, creator, legal notice) – Content description (title, summary, genre, concepts) 37 New trends in television: social and semantic
  38. 38. Why have metadata? Archives from where content has to be found and retrieved have been the place where the need for accurate documentation first arose. 38 New trends in television: social and semantic
  39. 39. Broadcast metadata • Data about data – All digital resources (A/V, scripts, contracts, reports, pictures, etc.) are data – Metadata is created at all stages in broadcasting from commissioning to playout • Three main categories – Administrative metadata • Replacing project and asset management paperwork – Technical metadata • Format, processing, identification, location, database, network – Descriptive metadata • All asset related information, human readable 39 New trends in television: social and semantic
  40. 40. Need for common standards Broadcaster Broadcaster Broadcaster TV Content NoTube 1 2 3 Creator 1 Exchange of information hampered by lots of proprietary interfaces TV Content TV Content TV Archive TV Archive n+1 Creator 2 Creator 3 1 2 40 New trends in television: social and semantic
  41. 41. EPGs Screenshot http://www.ifanzy.nl 41 New trends in television: social and semantic
  42. 42. EPG data • An EPG is composed of two parts: content descriptions and broadcast description • Content descriptions contain static data about television programmes such as a brand name (e.g. EastEnders), description or plot summary, type of programme, (e.g. series, movie, news), genre(s) (e.g. drama) actors, directors, recording data, etc. • Broadcast description is expressed by variable data, such as channel (e.g. BBC ONE), format (e.g. 16:9) and broadcast media (e.g. digital television) 42 New trends in television: social and semantic
  43. 43. TVAnytime (1/2) • Unique document structure – Program description – Program location – Program segmentation – User description & personalisation – System aspects – Content rights 43 New trends in television: social and semantic
  44. 44. TVAnytime (2/2) • Advantages of TV-Anytime – It is network and middleware independent – Supports related material, segmentation, locators, group information etc. • Applications of TV-Anytime – ARIB – DVB (MHP, DVB GBS, DVB IPI, DVB CBMS) – Asian User Groups, Korea – US’ Consumer Electronic Association – HbbTV 44 New trends in television: social and semantic
  45. 45. TVAnytime schema 45 New trends in television: social and semantic
  46. 46. Other models in use • egtaMETA - a unique metadata exchange schema dedicated for the exchange of ads between ads agencies and broadcasters. NoTube was an early tester of the schema in its personalised advertisements use case. • BMF – an abstract semantic model designed for metadata exchange in the professional media production domain. ARD in Germany is starting to use BMF. • Presto Space – format generated by the project of the same name to provide for digital preservation of audiovisual collections. Used by NoTube partner RAI. 46 New trends in television: social and semantic
  47. 47. Metadata interoperability via NoTube http://notube.tv/tv-metadata-interoperability/ for more information 47 New trends in television: social and semantic
  48. 48. BBC /programmes The BBC have made their EPG data machine- readable and published it on the Web 48 New trends in television: social and semantic
  49. 49. BBC /programmes: add .rdf http://www.bbc.co.uk/program http://www.bbc.co.uk/program mes/b00rl5y1 mes/b00rl5y1.rdf 49 New trends in television: social and semantic
  50. 50. BBC /programmes ontology This may the first TV content ontology, but certainly not the last! Key organisations in the TV standards domain are exploring the publication of metadata in RDF or SKOS: • EBU (Core) • TV-Anytime • IPTC (NewsML) The final step must be a common shared ontology integrating the different schemas (cf.W3C Media Ontology and API) From http://purl.org/ontology/po/ 50 New trends in television: social and semantic
  51. 51. Channel identifiers • Collected resolvable channel identifiers together with relevant metadata in RDF, e.g. 1700+ channel identifiers of Freebase http://www.cs.vu.nl/~ronny/notube/tv-channels.rdf 51 New trends in television: social and semantic
  52. 52. Genre taxonomies • BBC, TV Anytime, YouTube, IMDB, tvgids.nl … • Convert them into RDF concepts and define SKOS relations between them, e.g. EBU has done this for the TV Anytime Classification scheme 52 New trends in television: social and semantic
  53. 53. Concept extraction • NLP tools identify named entities in text and attach an unique identifier to them e.g. OpenCalais, Zemanta • Focus on key classes of entity such as person, place or organisation • Use of Linked Data for common concept identifiers • Ontotext developed specifically for TV metadata the tool LUPedia 53 New trends in television: social and semantic
  54. 54. LUPedia (http://lupedia.ontotext.com) 54 New trends in television: social and semantic
  55. 55. Concept extraction for TV 55 New trends in television: social and semantic
  56. 56. Linking TV content to Web content David Dickinson starring Tim Wonnacott birthplace Barnstaple 56 New trends in television: social and semantic
  57. 57. Pause 57 New trends in television: social and semantic
  58. 58. (3) Extracting knowledge about the user Idea: generating user profiles from data the user creates on the Social Web, and in this way facilitating a personalised TV experience without an intrusive user profiling process. 58 New trends in television: social and semantic
  59. 59. Facebook, Twitter & co. 59 New trends in television: social and semantic
  60. 60. Activity Streams • RSS/Atom feeds include a title, description, link and some other metadata; • Activity Streams extend this with a verb and an object type – to allow expression of intent and meaning – to provide a means to syndicate user activities • Supported by Facebook, MySpace, Windows Live, Google Buzz and… 60 New trends in television: social and semantic
  61. 61. 61 New trends in television: social and semantic
  62. 62. Getting TV into the Social Network „ BBC iPlayer adds Twitter and Facebook to socialise TV” – Share what you are watching on iPlayer – Sync viewing with friends – Real time chat Techcrunch Europe, May 26 2010 62 New trends in television: social and semantic
  63. 63. TV viewer actions • Recorded • Consumed • Loved • Bookmarked • … 63 New trends in television: social and semantic
  64. 64. Twitter activity 64 New trends in television: social and semantic
  65. 65. Bringing it all together 65 New trends in television: social and semantic
  66. 66. Eurovision example • Analyse tweets with the #eurovision tag over a set time period (during the program) • Extract country and positive/negative remark 66 New trends in television: social and semantic
  67. 67. Getting the user‘s interests 67 New trends in television: social and semantic
  68. 68. Beancounter architecture 68 New trends in television: social and semantic
  69. 69. FOAF • RDF based format http://xmlns.com/foaf/spec/ – Defines properties for describing a person and their relations to other people and objects 69 New trends in television: social and semantic
  70. 70. Weighted Interests • Add weighting to the foaf:interest property See http://xmlns.notu.be/wi/ 70 New trends in television: social and semantic
  71. 71. FOAF as common vocabulary 71 New trends in television: social and semantic
  72. 72. Beancounter web UI 72 New trends in television: social and semantic
  73. 73. Collecting user streams 73 New trends in television: social and semantic
  74. 74. Viewer profile (1/2) 74 New trends in television: social and semantic
  75. 75. Viewer profile (2/2) 75 New trends in television: social and semantic
  76. 76. (4) TV content recommendation • Recommender strategy – Collaborative recommendation • You share interests with your friends • Statistical analysis: what content is liked/watched quantitively more by others with similar interests/history – Content-based recommendation • An interest in X means a potential interest in Y • Pattern-based analysis: what content has related concepts to the content liked/watched by you – Hybrid recommendation • Best of both! 76 New trends in television: social and semantic
  77. 77. NoTube recommendation approach 77 New trends in television: social and semantic
  78. 78. Recommendation lifecycle Graphic by Libby Miller, BBC 78 New trends in television: social and semantic
  79. 79. Linked Data recommendations • The content-based approach: – Identify weighted sets (patterns) of DBPedia resources from user activity objects – Compute distance between DBPedia concepts in the user profile and in the program schedule through its SKOS-based categorisation scheme – Choose the matches above a certain threshold for TV programme recommendation 79 New trends in television: social and semantic
  80. 80. User interests (DBPedia concepts) 80 New trends in television: social and semantic
  81. 81. Match user interest and TV subjects 81 New trends in television: social and semantic
  82. 82. N-Screen http://n-screen.notu.be 82 New trends in television: social and semantic
  83. 83. Get recommendations 83 New trends in television: social and semantic
  84. 84. TV recommendation calculation 84 New trends in television: social and semantic
  85. 85. So, is this the future of television? More: http://notube.tv/showcases/personalised-news/ 85 New trends in television: social and semantic
  86. 86. Or this? More: http://notube.tv/showcases/tv-guide-and-adaptive-ads/ 86 New trends in television: social and semantic
  87. 87. Or this? More: http://notube.tv/showcases/tv-and-the-social-web/ 87 New trends in television: social and semantic
  88. 88. And in the farther future? 88 New trends in television: social and semantic
  89. 89. Interested in the project results? Find out more online at www.notube.tv All contents © NoTube project 2009-2012 No re-use of any slides or content of slides without explicit acknowledgement of: NoTube project, www.notube.tv & this slideset, www.notube.tv/slides 89 New trends in television: social and semantic

×