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3 Legal Mechanisms for Sharing Data
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3 Legal Mechanisms for Sharing Data


Presentation at the National Academy of Sciences Symposium on data citation, Aug. 22, 2011

Presentation at the National Academy of Sciences Symposium on data citation, Aug. 22, 2011

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  • Sharing data = easy. But lose control, including credit. Obvious if no license, contract or waiver. But true even if any one of those legal mechanisms is used.
  • Define terms. Attribution = legally-imposed, remedy is lawsuit. Credit = what we want. Citation = rooted in norms of scholarly communication, purpose to support with evidence, but now proxy for credit. Important starting point.Attribution ≠ expectations for credit or citation standards. When remedy is lawsuit, recognize incongruity.
  • Turn to the law. 3 main legal mechanisms. When data shared, possibility it won’t be properly cited.
  • Licenses and contracts impose attribution
  • Waivers do not. Consequences to each and will address each
  • Licenses – grant permission under conditions like BY
  • Sound like contracts
  • Built on underlying exclusive right. To understand scope of license, must understand right. Typically © or SGDR
  • © - bundle of rights
  • Automatic when fixed
  • Limited in scope and duration. Most important limit is © does not extend facts. No one can © fact, but can © collection of factsScientific data not subject © But collection of data could be
  • Line is murky, varies by countryEven where subject to ©, it only extends to original aspects and never facts. General rule = can extract facts from © database without infringing
  • Not in EU. They have SGDR. License can be © or SGDR, or both
  • Example = CCIF applied to database, license applies to data and databases, all to extent ©. Use of data that implicates © triggers attribution.Use of data that does not implicate © - e.g. if in public domain, does not trigger attribution.
  • Difficult to decipher © in scientific data and databases, hard to know when license applies. Creates risks.Risk that data provider be misledRisk that data user will under or over comply
  • Impose burdensome reqts – data from many sources, attribution stacking
  • Attribution reqts = inflexible. Absurd situations, must cite 1000 diff providers in 1000 ways. Could do all this and still not satisfy norms or expectations
  • Variety of names
  • Does not require underlying right, requires formalities, offer/acceptance, click thru, terms of use. Terms often require attribution.
  • Downsides = confusing obligations, no standardization, each user agreement has diff reqtsPeople may avoid data source b/c can’t understand the terms
  • Only binds parties, unlike licenses. Contracts more limited than licenses in that respect.If someone obtains licensed data and shares it, someone who obtains data from second user still bound by license. If data had been shared by contract alone, person who obtained data from second user would not be bound by contract terms b/c not party.In this respect, contracts more limited than licenses.
  • Broader reach than licenses. Not tied to right, can take away rights of public.
  • Example = Govt of Canada terms, violation if hurt rep of govt, was removed quicklyTroublesome. Esp when rarely read or negotiated.
  • Waiver. Can take many forms, but places in pd.
  • Not enforceable in all places. CCZero – 3 levels, waiver, fall-back license, non-assertion pledge.
  • Means no control. Can’t require attribution.But think back to probs with licenses and contracts. (attrib stacking, inappropriate obligations imposed on given community)Avoided when waiver used and relies on norms
  • Waiver provides legal certainty. No need to decipher © protection or sift through confusing legalese. If silent, people have to guess and may avoid b/c of risk of liability.
  • Summarize, each approach has consequences.
  • Licenses – (1) legal uncertainty about scope, (2) reqts that can be inconsistent with norms
  • Contracts – (1) burdensome reqts as each institution creates its own terms, (2) exceed scope of rights with reqts that take away rights of users.
  • Waivers – avoid problems. But lose control.
  • Each approach requires loss of control. No mechanism that imposes legally-binding obligations in way that perfectly maps to citation norms or academic expectations. By trying to use law, we risk unnecessary transaction costs on data sharing and pushing potential users away from our data.
  • Choosing right approach requires understanding consequences. Today’s conversations good start.


  • 1. 3 legal mechanismsfor sharing data { The limits of using the law to ensure proper credit Sarah Hinchliff Pearson Senior Counsel, Creative Commons August 22, 2011
  • 2. attribution ≠credit ≠ citation
  • 3. 1.licenses2.contracts3.waivers
  • 4. licenses & contracts require { attribution
  • 5. waivers do not { require attribution
  • 6. 1. licenses
  • 7. licenses ≠ contracts
  • 8. licenseright
  • 9. ©
  • 10. © = automatic
  • 11. © ≠ fact
  • 12. ©=?
  • 13. EU Sui generis database rights
  • 14.
  • 15. ©=?
  • 16. attribution stacking
  • 17. attribution ≠ norms
  • 18. 2. contracts
  • 19. contract right
  • 20. attribution ≠ norms
  • 21. contract < license
  • 22. contract > license
  • 23. 3.waivers
  • 24. waivers ≠ control
  • 25. waiver ≠ ?
  • 26. law ≠ perfect
  • 27. 1. ©=? 2. attribution ≠ normslicenses
  • 28. 1. attribution ≠ norms 2. obligations > rightscontracts
  • 29. 1. waiver ≠ controlwaivers
  • 30. law ≠ perfect
  • 31. Sarah Hinchliff Pearson, August 22, 2011 slide show licensed under the CC BY international 3.0 license