[Rdap] [RDAP] How much data should researchers *actually* publicly deposit?

[Jonathan Petters]

I'll add that I usually tell NSF proposal writers to say in their DMP that
they publicly share what data they're willing and able to. In many cases I
can get them to agree that at least sharing the data displayed in
figures/plots would be useful to their colleagues, and some are willing to
go further in sharing raw data and processing scripts.

To follow NSF's policy, I agree with Sebastian that if

   - the peer reviewers of your proposal are alright with your DMP (and
   what you say you will share),
   - the program officer is alright with your DMP, and
   - you eventually share what you say you will,

You're currently good with NSF. And really, the third bullet is a maybe at
this time; it's not clear NSF is really checking DMP compliance at present.
But they may in the future, and all the funding agencies say that
non-compliance with a DMP may count against a prospective PI in future
funding proposals.

-Jon

On Thu, Sep 6, 2018 at 8:33 PM, Sebastian Karcher <skarcher at maxwell.syr.edu>
wrote:

> Hi Kate and others,
>
>
>
> I think it’s important to remember that “The NSF” doesn’t really exist for
> this purpose. While yes, NSF has one overarching data policy (though
> directorates have slightly differing versions), in effect this is
> determined by a) the program officer and b) the (anonymous) selection
> committee
>
> Assessing whether there is enough data sharing is basically a three stage
> process:
> 1) We have seen a number of occasions now where program officers have
> actually sent the DMP back to the researcher and asked them to include more
> data sharing before sending the proposal out for review. Typically this
> happens with relatively short deadlines and is stressful, but it doesn’t,
> afaik, harm the proposal. It’s pretty clear that how much individual
> program officers push applicants on this varies a lot.
>
> 2) The grant selection committee does have access to the DMP and is
> actually required, by NSF rules, to comment on it in their recommendation.
> In many cases, they’ll just glance at it and sign off, but these are,
> typically peers, perhaps even competitors of the grant applicant and I
> cannot imagine them looking kindly on obvious attempts to withhold data “to
> maintain a competitive edge”. I.e. not sharing “enough” data in the eyes of
> their fellow scientists can absolutely sink a grant application.
>
> 3) Finally, the program officer reviews and has to sign off on the grant
> reports. We have strong anecdotal evidence that there is currently very
> little follow through on promises to share data, but there is, of course,
> no guarantee that is going to stay that well, and obviously, not having
> your grant report accepted is a big problem. (Needless to say, it’s also
> deeply unethical to make promises to share data that one does not intend to
> keep).
>
>
>
> I obviously have a bias against researchers who want to share as little
> data as possible, so take this with a grain of salt, but I do think that
> the above makes clear that trying to skirt by with a minimum of data
> sharing for an NSF grant is a risky strategy. I’d try to discourage it best
> I could even I didn’t believe it was *also *an ethically questionable
> strategy.
>
>
>
> All best
>
> Sebastian
>
>
>
>
>
>
>
> *From:* rdap-bounces at kunverj.com [mailto:rdap-bounces at kunverj.com] *On
> Behalf Of *Kate Barron
> *Sent:* Thursday, September 6, 2018 4:01 PM
> *To:* rdap at mail.kunverj.com
> *Subject:* [Rdap] [RDAP] How much data should researchers *actually*
> publicly deposit?
>
>
>
> Hi RDAP,
>
>
>
> When a project is funded by a federal grant, how much raw data are
> researchers expected to make accessible? Must they truly make everything
> and anything publicly available, or are brief extracts and/or summary
> statistics acceptable (in other words, what is the minimum sharing
> requirement)? What practices have you noticed among your
> colleagues/constituents?
>
>
>
> I am specifically looking at NSF grants, for which guidelines are
> (intentionally?) vague. I am working with a faculty member who is hesitant
> to share all of their data, as they want to maintain a competitive edge.
>
>
>
> Thanks for your input,
>
> Kate
>
> --
>
> Kate Barron
>
> Data Services Librarian
>
> Dr. Martin Luther King, Jr. Library
>
> San José State University
> kate.barron at sjsu.edu
> 408-808-2038 <(408)%20808-2038>
>
>
>
> Explore Data Services <https://libguides.sjsu.edu/dataservices> at SJSU
> King Library!
>
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>


-- 
Jonathan Petters Ph.D.
Data Management Consultant and Curation Services Coordinator
Data Services, University Libraries
Virginia Tech
(540) 232-8682
https://www.lib.vt.edu/research-learning/ResearchDataManagementAndCuration.html
ORCID: 0000-0002-0853-5814
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