This is a speculative talk (with narration on the download) considering the benefits of using Moz' OBI to support credit for sharing data, enhancing public databases and providing 'on the job' training. Please note that no commitment from Mozilla or any of the assessors described in the talk has been obtained thus far. This talk is intended solely to provoke discussion.

1. Rewarding contributions to public
resources with the Mozilla OBI
Chris Taylor
chrisftaylor@gmail.com

2. Context
• Data sharing in science is patchy at best
– Often done grudgingly (minimal effort)
– Avoided whenever possible
• Sticks are of little use
– Just enough effort to avoid getting hit
– Rarely deployed by funders anyway
• Carrots are few
– The ‘Piwowar (et al.) effect’ (more citations), but...
– Altmetrics are also limited in scope (and reach)
– Costs are immediate; benefits are deferred

3. What matters to scientists?
• Career, career, career.
– Research Excellence Framework (UK)
– Faculty assessment (everywhere)
• What counts on a CV?
– Right now, publications and little else
– In the future, (social impact of) other outputs
• And what (mostly) doesn’t?
– Annotating, sharing and curating data sets
– Training and supporting others

4. Why should they share?
• 2012 Research Data Management survey
– ‘Have you ever been inspired to undertake new or
additional research as a result of looking at data
that has been shared by researchers in the past?’
• Absolutely: 36.9%
• Maybe/ish: 21.7%
– But visions don’t inspire most people
• Enhancing the Piwowar (et al.) effect..?
– Better metadata (breadth/depth): more citations?
– But it’s still deferred (and hard to ‘see’)
MORE THAN HALF OF RESPONDENTS!

5. So what do ‘the few’ do?
1. Make it easy
– FigShare, Dryad, integration, better tools, etc.
– Altmetric, Plum Analytics, ImpactStory
– Guidelines, vocabularies, formats
– This is all progressing well
2. Make it count
– Record sharing (but...), curation and training
– Make such records visible to altmetrics
– REWARD EVERYTHING!

6. How do we do it?
• Credit where credit is due
– Tangible incentives → tangible effects (Darwin)
– Recognition must be robust over time
– Credible, widely accepted currency
• Conditions for success:
– Credit must be context-independent
– Issuing bodies need a framework
– Assessors must recognise them
– People must believe in them
– An obvious candidate is...

7. Open Badges Infrastructure
• This is a good candidate solution
– Robust systems already in place
– Portability in backpacks
– Many endorsements
• Not that there aren’t issues...
– Currently education/development-focused?
– Perceived as appealing more to the young
– Mark of achievement, not contribution
• But these are issues of perception

8. How would it work?
• Re-brand ‘backpacks’ as ‘electronic CVs’
– It’s the metadata and infrastructure that matter
• Re-brand ‘badges’ as ‘career credits’ (or..?)
– Rename and redesign to appeal to scientists
• This is not the tricky bit
• Work with major databases as exemplars
• Tricky bit #1 (who will go ‘first’? Some candidates...)
• Extract support from assessors
• Tricky bit #2 (but expressions of intent will do fine)
• Sociological bootstrapping is challenging

9. The Future (whoosh...)
1. YFNS makes a data set ready for submission
– Maximises value with structure/annotation, because...
– Anticipates credit from re-use (download?) by others
2. Submits to an OBI-compliant database (a market...)
– Receives ‘submitter credits’, stores in eCV
3. Adds value to existing records in a database
– Receives ‘curation credits’, stores in eCV
4. Trains an endless stream of students
– Receives ‘training credits’, stores in eCV
5. Advances career by demonstrating full worth

10. Thank you