barriers to direct collaboration - time, geography, limited technology people as entry points
&#x2018;liking&#x2019; items in FriendFeed being used successfully by chemists and other scientists to rapidly explore topics of interest more subtle &#x2018;gestures&#x2019; - e.g. the &#x2018;re-tweet&#x2019; in Twitter which points as much to the originator as it does to the resource or assertion they might have made
the AOL search data scandal in 2006 was widely reported as a breach of privacy, which it clearly was. But it also hinted at the extent to which users are increasingly present in systems. human richness of presence within these systems - not just data!! User 927 was identified by some as some disturbing &#x2018;attention&#x2019; patterns were revealed - but what was very interesting about this user record is that is appears to represent an account shared by three very different people. Works with Amazon because there is a credit card involved - in academia need incentive for not sharing
is this a bug or a feature? people rather than representations of patterns of behaviour
is it better to really satisfy niche networks with tailored services, rather than a generalised offering which doesn&#x2019;t really satisfy anyone equally? Barrier to creating bespoke apps has been reduced
1. (representations of
email@example.com UKOLN is supported by:
A centre of expertise in digital information management
2. people in systems
• (representations of patterns of aggregated usage) OR
• the development of data-centric approaches and
services which provide scholars with resources
targeted to their individual, personalised needs
• pervasive networking technologies which have
reduced some barriers to collaboration
3. resource discovery via other people
• ‘gestures’ indicating attention - enlightened self-interest
• direct human ‘presence’ rather than anonymous or
• is this what we mean by ‘digital society’?
• can a well developed & highly available social network
• the scholar is not always in a ‘social’ mood - they might
• much of recent technology-enhanced collaborative
enterprise depends on enlightened self-interest....
• ...this might not always apply
• will people demand more control over their own
• what do you know about me?
• can I reuse this data myself elsewhere?
• can I remove it from your system?
5. lessons from AOL
• anonymised user 4417749....
• ...or as her friends know her, Thelma Arnold
• user 927
• David said ‘… and the more we track, the better we
can adapt our service without your intervention.’
• perhaps I welcome the chance to intervene
• perhaps I want other people, known to me, to be
able to intervene on my behalf
7. niche/specialist networks
• recommendation systems being tried with some
apparent benefits being realised at undergraduate level
• but, in academia, beyond undergraduate it’s long tail
all the way!
• small networks based on people actually knowing each
• do academics work this way?
• economic/business drivers underpinning service design
may be changing
8. questions for service providers
• what can those who provide digital library services
offer the “long-tail” of academia?
• in which context(s) might the personal/social
network offer a good approach to resource
• when might the service built on aggregated,
anonymised attention data be appropriate?
• can these approached be integrated by service
providers, or is this task best left to the user or