Content of review 1, reviewed on August 06, 2014

The article is well written and contains all important information necessary to interpret and re-use the dataset. The extent and contents of the dataset are unique and an extremely valuable contribution to sea urchin taxonomy. Its comprehensiveness will certainly make it a milestone in 3D morphology data publishing. I highly recommend publication, and there are almost no corrections to make.

I did not check all datasets, of course, but those I downloaded were viewable without problems and of high quality.

Major Compulsory Revisions

None.

Minor Essential Revisions:

  1. The DOI of reference No. 7 is wrong (it's the same as the one of reference No. 20)

Discretionary Revisions

  1. It would be useful to include a short explanation of the differences between a 2D dataset and a 3D dataset.

  2. p. 2, last two lines: “The deposited files significantly extend the amount of data on sea urchins that are electronically available.” → change to “The deposited files significantly extend the amount of morphological data on sea urchins that are electronically available.”

  3. p. 3. Add two or three indicative references of sea urchins being used as model species. This helps readers to get an idea for what type of research urchins are commonly used

  4. p8. If possible, include a direct link to the datasets in morphdbase.de, not to the central page.

Level of interest An article of outstanding merit and interest in its field

Quality of written English Acceptable

Statistical review No, the manuscript does not need to be seen by a statistician.

Declaration of competing interests I declare not to have any competing interest.

Source

    © 2014 the Reviewer (CC BY 3.0 - source).

References

    Alexander, Z., Cornelius, F., Susanne, M., Nina, N., Leif, S. 2014. A dataset comprising 141 magnetic resonance imaging scans of 98 extant sea urchin species. GigaScience.