The American Naturalist has begun the process of creating a new editorial board position: 'Data Editors'. Their job will be to help facilitate and check compliance with the journal's open-data policies. We require publication of raw data and metadata on Dryad or equivalent public repositories, and we recommend including code to reproduce analyses. Exceptions can be made, to post the data but embargo public access for a set amount of time to allow authors to publish related papers, but we rarely get these requests.
It has come to our attention recently that compliance with our data policies is ... not quite as effective as we'd like. This mostly comes down to missing material in the posted data, or unclear metadata. To help authors do a better job of meeting our data publication expectations, I began a committee composed of Bob Montgomerie, Paulinha Lemos, and Rob Knell. They have produced the following Data Archiving Checklist, listing best-practices which authors may find useful in preparing materials for Dryad or other data archives. You may also find the DRYAD best practices list useful.
assemble all of your data files used to prepare your paper
ensure that every observation is a row and every variable is a column
if you analyzed means rather than the raw data, also supply a data file with the raw data from which those means were calculated
from each file remove variables not analyzed
identify each variable (column names) with a short name (no spaces or symbols), preferably <10 characters long. Use an underline (e.g. wing_length) or camel case (e.g., WingLength) to distinguish words if you think that is needed. See the Google R style guide (https://google.github.io/styleguide/Rguide.html) and the Tidyverse style guide (https://style.tidyverse.org/syntax.html#object-names) for more information
prepare a README file that lists all of your data and code files with a brief description of the file and a list of all variable names and an explanation of each variable so that someone else could understand what that variable means (including units). See Dryad suggestions here.
save the README file as a text (.txt) file and all of the data files as comma-separated variable (.csv) files
if your data are in EXCEL spreadsheets you are welcome to submit those as well (to indicate colour coding and provide additional information (formulas etc) but each worksheet of data should also be saved as a separate .csv file.
Save each file with a short, meaningful file name (see DRYAD recommendations here), except the README file which should just be called README.txt
save all image, audio, and video files in formats recommended by DRYAD (here). You may wish to contact DRYAD or your Editor if the raw data files are too large.
upload all of your files to DRYAD or other repository and fill in all of the metadata and information requested by the repository, even if this is not required as it makes your data easier to find and understand
from the repository get a URL that can be used by editors and reviewers before your data are made public with a DOI
last updated 7 September 2020