1. data sharing and the
polar information commons
kaitlin thaney
program manager, science
creative commons
This presentation is licensed under the CreativeCommons-Attribution-3.0 license.

2. access is step one
content needs to be legally and
technically accessible

3. knowledge?
journal articles
data
ontologies
annotations
plasmids and cell lines

4. knowledge?
journal articles
data
ontologies
annotations
plasmids and cell lines
... how to treat? like content? software?

5. as a means to achieve Open Access

6. data? not necessarily.
(it’s complicated)

7. copyright and databases
what’s protected? is it legal?
facts are free
to what extent is there creative
expression?

8. the data “rights” conundrum...

9. ©
“creative expression”

10. is it creative?

11. is it creative?

12. is it creative?

13. category errors

14. the problem of...
Non-Commercial
for data

15. Non-Commercial
what’s a commercial use
of the data web?

16. the problem of...
Share Alike
for data

17. 1854

18. issue of license proliferation
whatever you do to the least of the
databases, you do to the integrated system
(the most restrictive wins)
risk for unintended consequences

19. the problem of...
Attribution
for data

22. the problem of...
any license
for data

23. national law / jurisdiction-based
hurdles
sui generis,
“sweat of the brow”
Crown copyright
“level of skill”
how internat’l data sharing efforts
are affected?

24. attribution vs. citation
which one applies? which is best fit?
what’s the difference?
“credit where credit is due”

25. attribution:
(legal entity)
“triggered by making of a copy”
does it apply to facts?
how to attribute? (papers, ontologies, data)
“in a manner specified by ...”
attribution stacking

26. citation:
(gentle(wo)man’s club)
legal requirement?
interoperability?
credit where credit is due
entrenched scientific norm

27. we shouldn’t use the law to make it
hard to do the wrong thing ...

28. need for a legally accurate and
simple solution
reducing or eliminating the need to make the
distinction of what’s protected
requires modular, standards based approach
to licensing

33. ... must promote legal predictability and certainty.
... must be easy to use and understand.
... must impose the lowest possible transaction costs on
users.
full text:
http://sciencecommons.org/projects/publishing/open-access-data-protocol/

34. norms approach
set of principles (not license)
open, accessible, interoperable
create legal zones of certainty

35. calls for data providers to waive all rights
necessary for data extraction and re-use
requires provider place no additional
obligations (like share-alike) to limit
downstream use
request behavior (like attribution) through
norms and terms of use

36. Creating norms for polar data
1. How to preserve the source information? How should the user or
copier preserve the provenance of the data set. What can be required
by PIC that is locally relevant and acceptable? DOIs? Something like a
notice inside the data? Ping to a URL at PIC? RDFa inside a section of
every database that is provided by PIC?
2. How to cite the data set? Many examples out there including
http://ipydis.org/data/citations.html
3. How to preserve quality standards? Perhaps we leave it up to the
users?
4. How to note and release user contributions, mashups, repurposing?
Do we need release guidelines of contributions, annotations, etc. to
data sets. How to reward and track individual contributions to a
collective - trackback, user accounts, etc.? A simple “share alike”
request?

37. Some draft norms of appropriate scientific
behavior when using PIC data
• Acknowledge the source of the data in accordance with the wishes of the provider,
and explicitly cite the data when they are used in formal scientific publication (http://
ipydis.org/data/citations.html).
• Maintain a link to the original information in any derived products, ideally through a
persistent identifier, such as a Digital Object Identifier.
• Understanding that the data are made available “as is” and the accuracy of the data
or documentation are not guaranteed. The provider assumes no responsibility for
misuse or misinterpretation.
• Notify the data provider in the manner they describe on how you plan to use the
data. For projects integrally dependent on the data consider requesting
collaboration and/or co-authorship from the provider.
• Share any derived products in the PIC.
• Agree to IPY Data Policy
37

38. others?

43. 5.4 million bibliographic records

45. at best, we’re partially right.
at worst, we’re really wrong.

46. data without structure and annotation is a
lost opportunity.
data should flow in an open, public, and
extensible infrastructure
support recombination and reconfiguration
into computer models, queryable by search
engine
treated as public good

47. resist the temptation to treat
as property
embrace the potential to treat instead
as a network resource