Hi,

I have not received a similar query, but as someone who has received Royal Society funding in a "non-data generating" discipline (before the introduction of the data management plan) and has at least basic familiarity with the rationale for introducing data management plans, maybe my perspective will be useful.

Let's say for the sake of argument that the discipline in question is something like mathematics, theoretical computer science, or theoretical physics, where the researcher is totally correct in assessing that their work will not lead to data that needs to be preserved (separately from research papers presenting the results).  In this case I would expect that it would be totally acceptable for the "data management plan" to be one line, something along the lines of "The planned research will not generate data that needs to be archived; all research results will be captured in archival publications".

If it's more of a gray area, as suggested by the mention of "protocols" that do need to be preserved in order for others to build on the research, then I would view these as potentially "data" that should be preserved.  In particular, if the research is based on creating computational models, then a narrative description of how the software works is not always enough for reproducibility and planning to preserve/archive the code would be in order.  (The Software Sustainability Institute has a lot of resources on that.)

However, if these protocols are routinely published in research articles in ways that enable them to be fully reused by others then I would think the one-liner above explaining this would suffice.

Speaking as a researcher, I would not see the point in generating "metadata without data".  This sounds like pure make-work to me and researchers already have plenty of that.  I could even imagine reviewers wondering why the person is proposing to waste time on creating metadata instead of doing more actual research.  But I would encourage the researcher to take a broad view of what the "data" could be (i.e. anything needed for others to understand and reuse the research that is not captured in publications) and have a clear rationale for why no preservation is needed that will stand up to scrutiny from experts in related areas, just like any other part of the proposal.

--James

> 
> Date:    Sun, 22 May 2016 08:07:27 +0000
> From:    "Rzepa, Henry S" <[log in to unmask]>
> Subject: Q: Is it neccessary to manage research data if there is no data? (A: yes!).
> 
> I was asked by a young researcher a few days ago about RDM.  She is applying for a Royal Society grant, and as she put it, "they have introduced a new section regarding data management…  This is oddly the largest section in the application and I wouldn't be generating large amounts of … data ...”
> 
> She works in one of those areas where the data is mostly the “procedures” used, and these procedures are described in full in the research narrative rather than being constituted as separate data (files). Her basic question was that if the narrative is essentially also the data, was there any need for explicit data management? 
> 
> I am pondering how to reply to her, so far along these lines.  I am interested if anyone else on this list has received similar query, and indeed how they have answered them.
> 
> A: From my point of  view, RDM is not entirely all about data, it is actually much more about metadata!   And you can have metadata WITHOUT data.  So even if a project generates no explicit (or apparent) data, it can still generate the metadata (in this case about the procedures being described). And of course there is lots of metadata present by default, thus the date claimed for deposition of metadata, the  ORCID of the researcher(s), the institution were the data was generated and “associated DOIs”.   And all this metadata can itself be described by metametadata, ie a suitable persistent identifier such as a  DOI. 
> 
> So my answer is likely along the lines that it is always worth generating even a minimal amount of metadata, and depositing only that, to get in return a  DOI which can then be quoted in any articles, submitted to the  institution’s CRIS, and of course sent to eg  DataCite where it can then be discovered/aggregated and generally rendered as a visible outcome of the research.  All without actually submitting any data itself!
> 
> Henry
> 
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> 
> End of RESEARCH-DATAMAN Digest - 21 May 2016 to 22 May 2016 (#2016-105)
> ***********************************************************************
> 


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