Open Data & The Panton Principles: Thoughts on a presentation to librarians

As I mentioned last week, on Tuesday, April 17 I was part of a workshop on Creative Commons our Scholarly Communications Committee put on for York library staff. My section was on open data and the Panton Principles. While not directly related to Creative Commons, we thought talking a bit about an application area for licensing in general and a specific case where CC is applied would be interesting for staff. We figured it would be the least engaging part of the workshop so I agreed to go last and use any time that was left.

Rather unexpectedly, the idea of data licensing and in particular CC0 licensing for data ended up being the topic that most energized the crowd! So we bumped up my part and I ended up going second-to-last. My section sparked a lot of very interesting conversations and feedback from a pretty packed house.

So much so, that while riding home on the bus on Friday with a colleague, she mentioned that the issues I'd talked about on Tuesday had come in handy at the conference she'd attended on campus earlier on Friday. She'd been able to speak intelligently and provocatively about the usefulness of open data to public policy!

So, a huge win.

Lessons learned? I think if I were doing the presentation over again tomorrow, I'd emphasize the practice of making data openly accessible should be considered as outside the normal scholarly communications system. It isn't just for pirates and thieves. The goal is to make data sharing a standard practice. The means to that end is to ensure data sets are cited in the literature and by extension to have data sharing become an accepted part of the normal academic reward and incentives structure. You create data, you share it, someone else uses it for their research, they cite your data set in their paper, that citation is counted with the same weight as a citation to a paper.

And within that understanding, I think I also would have emphasized more that it's just the right thing to do. Sure, you can fear being scooped with your own data, that someone will replicate your claims and try and take the credit, sure someone might even try and claim that they created your data themselves. But these "risks" should be seen as no different from the risks of publishing anything -- a journal article, a blog post, some code.

But those are far outweighed by the great potential of making scientific data open.

In any case, that's for next time. And hopefully there will be a next time. We're definitely hoping to take our workshop to a conference somewhere.

I don't believe any of the other presentations by my colleagues are online, but I'll link to them here if I find them.

And speaking of presentations, here are my slides:

I'll note that I'm waiving all rights to the slides and releasing them with a CC0 waiver. So have at them!

Also, here are the resources I used for my presentation as well as a few more that have come to light since my original post.

• The Panton Principles
• Why does Dryad use CC0?
• #sparc2012 a manifesto in absentia for Open Data
• Information mining from Springer full-text: I ask for freedom
• Textmining Update: Max Haussler's Questions to publishers: They have a duty to reply
• The CONTROL of knowledge: Ours or Elsevier's; It's High Noon for Universities
• Our Protocol for Text-mining: Preamble and "Institutionalism"; Elsevier and other publishers should take note
• Elsevier, Nature and Content-mining - yet another Digital Land Grab - wake up academia and fight. Or surrender for ever
• They. Just. Don't. Get. It...
• Computing availability of full text for reuse
• Talking Text Mining With Elsevier
• Elsevier responds to my text mining request
• Open Data Is Not Your New Bicycle
• Why we should publish our data under Creative Commons Zero (CC0)
• Can't I just say "data available for educational and research use"?
• Why should data be released under the CC0 waiver...
• Remembering Babel: Open Data Sharing & Integration
• The Conundrum of Sharing Research Data
• Extracting, Transforming and Archiving Scientific Data
• Why don't scientists share data?
• Who Shares? Who Doesn't? Factors Associated with Openly Archiving Raw Research Data
• Why don't scientists share data?
• Who Shares? Who Doesn't? Factors Associated with Openly Archiving Raw Research Data
• Data sharing: Empty archives
• Nature special issue on data sharing (September 2009)
• Science special issue on data sharing (February 2011)

And some new ones:

• Ensuring the Integrity, Accessibility, and Stewardship of Research Data in the Digital Age
• BioMed Central's position statement on open data
• Creative Commons Licences (good overview from JISC with pros & cons)
• Elsevier agrees UBC researchers can text-mine for citizen science, research tools
• The Digital Public Domain: Foundations for an Open Culture
• Do we need a text-mining manifesto?
• BioMed Central article collection on Data standardization, sharing and publication
• Trials journal collection on Sharing clinical research data
• Text-Mining Is The New Front, Ready To Escalate Issues Triggered By RWA Debacle
• Why share research data?
• OECD Principles and Guidelines for Access to Research Data from Public Funding
• Identifying benefits arising from the curation and open sharing of research data produced by UK Higher Education and research institutes
• To Share or not to Share: Publication and Quality Assurance of Research Data Outputs
• Wellcome Trust data sharing page
  • Data management and sharing policy
  • Guidance for researchers
  • Public health and epidemiology
  • Large-scale genetics research
• A review of journal policies for sharing research data
• Research Data: Who Will Share What, with Whom, When, and Why?
• Data sharing in astronomy
• The Sixth Data Release of the Sloan Digital Sky Survey

As before, any suggestions for further resources would be greatly appreciated in the comments.