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Instant Messaging & Presence

Instant Messaging & Presence. Marc Eisenstadt, Stuart Watt Knowledge Media Institute OU Learning & Teaching Innovation Committeee 6 th February, 2002. 84 million active accounts. 70 million registered users. 61 million registered users. 65 million downloads since fall 1999.

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Instant Messaging & Presence

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  1. Instant Messaging & Presence Marc Eisenstadt, Stuart Watt Knowledge Media Institute OU Learning & Teaching Innovation Committeee 6th February, 2002

  2. 84 million active accounts 70 million registered users 61 million registered users 65 million downloads since fall 1999 What Do These Have in Common? • Hotmail • ICQ +AIM • Napster+Morpheus+ ...The fastest-growing apps in history!

  3. Person-to-person asynchronous messaging Peer-to-peer Person-to-person real-time messaging Peer-to-peer Person-to-person real-time messaging Peer-to-peer Person-to-person file sharing Peer-to-peer What Else in Common? • Hotmail • ICQ +AIM • Napster+Morpheus+ People are the key

  4. Typical IM session

  5. FirstClass chat Not the same as chat Presence‘radar alert’

  6. Many varieties; similar concepts • ICQ • AOL Instant Messenger • Yahoo! Messenger • MSN Messenger • Odigo • Trillium • Jabber (open source, XML-based)

  7. Key insights • We can harness wild popularity (people use it anyway, but big outfits have own solutions) • ‘Always on’ is not required: just assume ‘improved access’ (e.g. flat-rate phone charges) • Accept inter-operability • Encourage ‘enhanced presence management’ (e.g. lightweight ‘radar’)

  8. BuddySpace • KMi’s current experiment in presence management • Partly EPSRC-funded (begins May 2002) • Automatic map construction to show locations • Automatic roster construction using OU’s LDAP and SAMS authentication… so it knows which workgroup or tutorial group I’m in • Many views: map, timelines, etc.

  9. Plain chat Automatic rosterconstructionduring login =personal tutorgroup, work groupetc. Embeddedbrowser for custom ‘newsflashes’ etc.

  10. Typical view ofOU tutorial group Automatic rosterconstructionduring login =personal tutorgroup, work groupetc.

  11. Automatic mapconstructionfrom user data

  12. Smart inset chosen,depending onactual data

  13. Map & faces arecustomised; dotsdisplay true status

  14. Floorplan of KMi; Dots are those ofinterest to me

  15. OU campus map

  16. World, Europe,KMi floorplanall together

  17. Timeline view, e.g. which TMA?

  18. What next? • Several course teams already expressing interest • An ‘agnostic’ client can be built (emphasises the ‘popup radar’/dashboard aspect, then chat takes place using FirstClass, MSN Messenger, etc.) • Worth OU investment • Trials needed

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