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NoTube - Experimenting with Linked
Data to improve user experience
Vicky Buser, Information Architect
September 3rd, 2010 – SSMS’10

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NoTube is an example of using Linked Data for user-
facing apps as these two short videos explain…
1. Strategy & Direction
2. Highlights 11231965for each area
http://vimeo.com/11232681
http://vimeo.com/11231965

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A bit about my background…

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I’m an Information Architect

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The BBC and the semantic web
Some background

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It started with the BBC Programmes site…

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…following Linked Data principles, it ensures ONE page
per programme
http://www.bbc.co.uk/programmes/b00tllj9
http://www.bbc.co.uk/programmes/b00tjfys
http://www.bbc.co.uk/programmes/b00tjflh

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And it uses the BBC Programmes Ontology
Drawing borrowed from Michael Smethurst at the BBC

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Similarly, each artist in BBC Music has an RDF
representation

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BBC Wildlife Finder provides a URI for every species,
habitat and adaption

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The BBC’s World Cup site uses RDF and Linked Data to
build and manage the site of 700 aggregation pages

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The NoTube Project
Networks and Ontologies for the Transformation and
Unification of Broadcasting and the Internet

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NoTube is part of the wider trend of TV and Web
convergence

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The BBC is leading one of the Use Cases in NoTube

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The BBC’s Use Case: TV and the Social Web
demonstrates APIs for linking the Social Web with
broadcast and on-demand television, using linked data
from broadcasters, audiences and across the web, to
help make social content navigation applications and
active TV communities.

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Focus of the rest of this talk
How we can use linked data to improve the user experience

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Some observations relating to TV watching…

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1) Deciding what to watch on TV is hard

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2) People would often like to know more about a
programme they’re watching (e.g. BBC Red Button)

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3) Watching TV is still predominantly a social activity

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From a recent (Aug 2010) YouGov/Deloitte report
• 42% of those UK adults who use the Internet while
watching television do so to discuss or comment on
the programmes they are watching at the time.
• http://today.yougov.co.uk/consumer/television-going
-social

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So, how can we use Linked Data to help people to…
• Decide what to watch
• Discover more information related to a programme
• Have smarter conversations and social engagement
around TV programmes

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In our part of NoTube we are using three core techniques
to help with this…
• Dereferencable URLs
• Semantic enrichment
• Social APIs

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1) Using dereferencable URLs to identify programmes

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2) Enriching programme metadata with Linked Data
from the Web
• Using Ontotext's LUPedia and NoTube’s vocabulary
alignment service to:
– Add background knowledge and context
– Make new connections
– Support serendipity

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3) Linking the dereferencable URLs with Social APIs
• The idea is to connect people, their friends, their
activities, and their televisions in a suitably privacy
-preserving way in order to make TV in the future a
more enjoyable and interesting experience.
• E.g. by creating linkage points into social network
discussions, as well as shared bookmarking and
commenting systems
• Using Semantics to enhance the data
• Using community features for smart sharing and
discussions

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Our experiments…
What we’ve been doing

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Deciding what to watch – recommendations/filters
POTENTIAL UX BENEFITS OF USING LINKED DATA
• Recommendations are pushed in unobtrusive manner
• Interesting explanations provide context
• Can surface programmes of interest buried in the long-tail

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Interesting explanations…

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Surfacing programmes of interest buried in the long-tail

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Recommendations – Year 1: matching up graphs

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What we learnt…
• DBPedia-based recommendations not specific enough -
“Eastenders recommended because you like programmes
made in the 80s”
• Recommendations based on BBC’s Lonclass might
produce more interesting and useful results because
Lonclass is:
– more TV-centric
– more granular
– used by human indexers
BUT it’s BBC-centric

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Recommendations – recent Lonclass work
• DEMO: Two-screen prototype for web-based on
-demand video

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Recommendations – some challenges
• Generating interesting links is difficult
• We can't do Lonclass-based recommendations for
recent content

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Recommendations - what’s next?
• Reverse engineering user recommendations data to
discover more about what makes interesting links
• Looking at auto-classification of recently broadcast
programmes with Lonclass
• Mixing and matching Lonclass and other
recommendations work with social influencers
• Testing

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Recommendations – reverse engineering interesting links
Users A, B and F
like programmes
1 and 5 which are
both about
Amsterdam,
therefore location
might be
interesting to
users…

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Or the pathways through the graph could be further
apart…

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Recommendations – mixing with social influencers
• Such as:
– Twitter TV trends amongst my friends
– What my friends are watching
– What's most popular on Twitter right now

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Cross-domain recommendations

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Bearing in mind privacy implications

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Finding out more about a programme
POTENTIAL UX BENEFITS OF USING LINKED DATA
• User is pushed relevant background information
• User doesn't have to search for anything
• Supports content discovery/broadens knowledge
• User is in control: now or later

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Finding out more – in our year 1 demo

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Finding out more – what we might do next

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Creating the infrastructure to support online social
activity around video content
POTENTIAL UX BENEFITS OF USING LINKED DATA
• Unique URLs support UGC
• This enables all sorts of things to happen – “like
electricity”

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Creating the infrastructure: Libby’s Resolver
• Goes from broadcast TV to a webpage describing
what's on
• http://blog.notu.be/2010/08/26/connecting-broadcast
-tv-and-the-web-using-a-resolver/

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Creating the infrastructure – what’s next
• Starting by linking up disparate sources of programme
data internally within the BBC
• Good business value for the BBC and good for end
users
• Deep/rich links into a part of the content, to provide a
unique identifier for a particular in-programme event
• Developing APIs for social TV apps

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Summary and conclusions
Within the context of the NoTube project , Linked Data
techniques can improve user experiences by…

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Supporting content discovery and serendipity
• Follow your nose
• Find new video content
• See related information
• Find people with similar interests

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Reducing the burden of choice
• Automatically filtering of programmes of interest
• Delivering a more personalised experience

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Allowing for smarter conversations around video
content
• *This* is what I'm talking about
• I like/don't like/recommend/disagree with *this*
• *Here's* the evidence - using video rather than text to
explain things

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Call to action
For maximum impact, consider how your
work relates to real-world scenarios
and how it can be used to improve the
user experience

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We start the process by making storyboards

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Now, over to you…
• Postcards and stickers to give you inspiration!

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Further reading
• http://www.bbc.co.uk/ontologies/programmes/2009-09-07.shtml
• http://www.bbc.co.uk/blogs/bbcinternet/2010/07
/bbc_world_cup_2010_dynamic_sem.html
• http://blog.dbtune.org/post/2009/10/27/Music-recommendation-and
-Linked-Data
• http://blog.notu.be/

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Photo credits
• http://www.flickr.com/photos/mcfarlandmo/3275419562/in
/set-72157613720528518/
• http://www.flickr.com/photos/d-reichardt/4348924495
• http://www.flickr.com/photos/adambowie/2924076825/
• http://www.flickr.com/photos/disaster_area/3959753968/
• http://www.flickr.com/photos/nnova/2341090921/

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Thank you
• Questions/comments