1. Why we Metadata
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2. +
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3. +
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4. Why Metadata?
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5. Data Metadata
Cost side
Example: BBC Question Time 23/09/2010 - data sizes
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6. Data Metadata
Cost side
Example: BBC Question Time 23/09/2010 - data sizes
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7. Data Metadata
Cost side
Example: BBC Question Time 23/09/2010 - data sizes
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8. Data Metadata
Cost side
Example: BBC Question Time 23/09/2010 - data sizes
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9. Data Metadata
Cost side
Example: BBC Question Time 23/09/2010 - data sizes
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10. Data Metadata
Cost side
Example: BBC Question Time 23/09/2010 - data sizes
Programme
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11. Data Metadata
Cost side
Example: BBC Question Time 23/09/2010 - data sizes
Programme
Segments
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12. Data Metadata
Cost side
Example: BBC Question Time 23/09/2010 - data sizes
Programme
Segments
Subtitles
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13. Data Metadata
Cost side
Example: BBC Question Time 23/09/2010 - data sizes
Programme
Segments
Subtitles
Tweets
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14. Data Metadata
Cost side
Example: BBC Question Time 23/09/2010 - data sizes
Programme
Segments
Subtitles
Tweets
Interactions
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15. Revenue side
possibilities - TV
Data
• Passive viewing of full
content
• Schedule-based discovery
• Advertising targeting based
on content demographics
• Content commissioned
based on surveys and
samples
Metadata
• Segmentation of content
• Many modes of discovery
• Search
• Content-based
• Personalised guides
• Social context
• Highly targeted advertising
• Commissioning/product
development based on detailed data
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16. “find, play, share”
"give people the power to share"
“be the pulse of the planet,”
“organize the world's information”
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17. Things We Have Made
2007 20102008 2009
Project Pink
Totem
Social Media Guide
Test Tube Telly
Come Dine With Me Homemade Project Red
Amplus
WatchSomething
VoteUp/Gawp
URIplay
Atlas
Project Purple
Project Blue
Project Teal Project Orange Project Brown
Project Black Project Pale
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18. 2007 20102008 2009
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19. realtime video
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20. Tuesday, 30 November 2010

21. Tuesday, 30 November 2010

22. Tuesday, 30 November 2010

23. 2007 20102008 2009
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24. Tuesday, 30 November 2010

25. 2007 20102008 2009
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26. Tuesday, 30 November 2010

27. 2007 20102008 2009
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28. Tuesday, 30 November 2010

29. Tuesday, 30 November 2010

30. How does this metadata
fundamentally increase the value
of the content?
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31. Tuesday, 30 November 2010

32. Things we’re thinking about
• Mining relevance, and value out of archives
• Working with tastemakers
• Seamless collection of preferences to:
• Re-activate users
• Extend journeys (inc ads)
• Optimise pricing
• Joining interaction data from across disparate systems
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33. How can we efficiently produce
better metadata?
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34. Things we’d like #1
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35. Things we’d like #1
Better names
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36. Things we’d like #2
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37. Things we’d like #2
Important
timeline data
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38. Things we’d like #3
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39. Things we’d like #3
Meaning
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40. Why we Metadata
Presentation available at:
http://www.slideshare.net/
simsocast/why-we-love-metadata
Chris Jackson / @adrideo
CEO - MetaBroadcast
chris@metabroadcast.com
So long, and thanks for all the pictures ):
• http://www.flickr.com/photos/blahflowers/3713933900/
• http://www.flickr.com/photos/uwehermann/132244826/
• http://www.flickr.com/photos/dailyinvention/497294952/
Photos are used under a creative commons commercial licence
Thank you!
Tuesday, 30 November 2010