Sharing at 100%

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Transcript of Sharing at 100%

Conference 26-27th March 2013 University of Nottingham, UK

Sharing @ 100%? – arguments for a less selective approach to reporting OER activity

Chris Pegler, The Open University

Gema Santos-Hermosa, Open University of Catalonia

Anna Comas-Quinn, The Open University

Sharing and the ‘open landscape’

Made using Wordle – open licensed (thanks to Jonathan Feinberg who made it so)

Who are we ‘open’ with?

We might share 100% of what we generate with ourselves (even the unpublished stuff) but how about with others? How selective do we become as proximity reduces?

Zones of proximityPegler, 2011

Things we might select to share?

• Looks good or exceptional (showcase quality)• Rare/unusual/topical topic/treatment (high demand)• Makes you/yours look good (what works well here)• What you have ready to share (quick and easy)• Requirement or reward linked to sharing (funding)• We want/need a wider response to it (community)

These factors appear to apply whether sharing is of resources for education or research.

Resources we don’t select to share?

• Not usual/desired finish or quality (looks bad)• Lots of similar items already available (derivative)• It didn’t work as expected/planned (dirty linen)• Not finished, still work-in-progress (stalled)• No support or system to do this (costly)• We’d prefer no-one else finds out about it (amnesia)

Could there be good reasons in terms of education or research if openness is target?

Open knowledge exchange

Consider dissemination bias if we over-select:In medicine it is increasingly recognised that outcomes and data which projects choose not to formally publish may have benefit. Song, et al., 2010 suggested there may be dissemination bias in terms of what is published and shared.

So only some medical trials were shared. Not those with undesirable results or ones which were set aside.

Song F, Parekh S, Hooper L, Loke YK, Ryder J, Sutton AJ, Hing C, Kwok CS, Pang C, Harvey I, (2010). Dissemination and publication of research findings: an updated review of related biases. In Health Technology Assessment Feb;14(8):iii, ix-xi, 1-193.

Questions for you

Would you share openly resources which were:1. Not the usual/desired finish or quality (look bad)2. Similar to items already available (derivative)3. Didn’t work as expected/planned (dirty linen)4. Unfinished, still work-in-progress (stalled)5. Without established support/system to do this

(extra time or resource)6. Evidence of mistakes or dead ends/wrong turns

(revive bad memories)Would you find this useful if shared?

These are the problems we see

1. Adding yet more material to the mix (overload)2. May be not rigorously tested (unreliable)3. May be dead ends for good reason (waste time)4. May be insufficient to be of use (incomplete)5. Could damage image of provider (reputation)6. Not enough time/resources to do this (reward)7. How to curate this? How to search it? (systems)8. ???

What else have we missed?

Thank you for answering!

Thank you for listening

Have a great conference

Learn (ask) what’s behind the published (pursue open knowledge)