Data Sharing and the Polar Information Commons
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1. The document discusses challenges with applying traditional copyright licenses to data and proposes establishing norms rather than licenses to govern data sharing. 2. It suggests norms that promote open, accessible, and interoperable data by waiving all rights necessary for data extraction and reuse, while encouraging attribution and quality standards through terms of use rather than legal requirements. 3. The document argues that data should flow freely in an open infrastructure to support new uses and insights, and that data has more value when structured and annotated within such a system rather than treated as a private property.
Data Sharing and the Polar Information Commons
- 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...
- 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