fdschneider / bexis_traits

developing a trait data framework for use in the Biodiversity Exploratories
0 stars 0 forks source link

journal choice #24

Closed fdschneider closed 4 years ago

fdschneider commented 7 years ago

Our list of potential journals:

  1. Methods in Ecology and Evolution, as full article or an exceptionally long 'Application' article; high visibility for trait-based research in ecology
  2. Plos ONE; highly accessed, but low visibility; will require more PR work on our side
  3. Natures Scientific Data as an Article; not sure if it fits the scope.
  4. Pensoft Biodiversity Information Science and Standards or Biodiversity Data Journal; rather invisible for ecologists

Any other suggestions? The audience for the paper after all are ecologists with a trait-based focus, not information scientists.

caterinap commented 7 years ago

Someone also suggested Functional ecology, as the Moretti paper. Would also be good for visibility.

fdschneider commented 6 years ago

Any recommendations for reviewers? My top list so far:

nadjasimons commented 6 years ago

From my trait-literature:

I don't know what Cynthia Parr has worked on, but the other two fit.

caterinap commented 6 years ago

See this: https://methodsblog.wordpress.com/2017/11/29/software-review/

caterinap commented 6 years ago

One more potential reviewer:

fdschneider commented 6 years ago

The rOpenSci review is very thorough it seems and would be very valuable. However, just as for CRAN it requires to make the package build without errors and warnings and provide testing via testthat, integrated testing for all platforms (via TRAVIS) and so on. I need (much) more time for this.

Given that my time for working on it is very limited, I start to think that the best strategy for this would be

We can submit the paper without having all issues on the vocabulary and R package worked out, selling those as preliminary (as we currently do). But MEE will most likely not accept the manuscript containing the R package with all these open issues.

What do you think?

fdschneider commented 6 years ago

If the paper is turned more into a review of current initiatives for trait data standardisation, we definitely could try to submit it as an Review article (MEE or Functional Ecology), containing a draft of the vocabulary and a minimal reference to the R package under development.

caterinap commented 6 years ago

For sure the complete testing will take some time but most warnings/errors are usually small things. MEE seems to accept preprints Preprint policy so why not! I also quite like the idea of the review article and a smaller mention to the package (or even a second application paper to present the package), but this would also require a little more work on the paper as well (right now it's an hybrid), and we should make sure that the trait standard is well highlighted if we want people to use it. So for now I think that it's reasonable to proceed as you propose.

Small side note, I just saw this (R package ‘traitfindr’ that could be used to interrogate trait databases). It's not on git but can maybe be a source for reviewers as well.

nadjasimons commented 6 years ago

I finally found the time to look at the rOpenSci review process and the different article types with MEE in detail. I also think that rOpenSci would be a very valuable resource for feedback on the Rpackage. As far as I understood the information on the MEE website, the rOpenScie review is employed only for submissions as 'Applications'. For this, the manuscript is much too long right now and contains too much background and probably not enough examples of how one would use the package. Therefore, I agree that it might be best to restructure the manuscript as a Review article (might need a short 'Methods' section) --> submit it to PeerJ until the package is ready or --> directly submit it to MEE and work on a separate 'Applications' paper for the Rpackage. The traitdata standard and the thesaurus are already an important step towards more standardized traits and can be used by others without having the Rpackage.