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NoTube - Experimenting with Linked Data to improve user experience

Vicky Buser, Information ArchitectSeptember 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 & Direction2. Highlights 11231965for each area

http://vimeo.com/11232681http://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/b00tllj9http://www.bbc.co.uk/programmes/b00tllj9

http://www.bbc.co.uk/programmes/b00tjfyshttp://www.bbc.co.uk/programmes/b00tjfys

http://www.bbc.co.uk/programmes/b00tjflhhttp://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 indexersBUT 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…

• NoTube 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