Reviewer has chosen to be AnonymousOverall Impression:
UndecidedTechnical Quality of the paper:
Clear noveltyData availability:
All used and produced data (if any) are FAIR and openly available in established data repositoriesLength of the manuscript:
This manuscript is too long for what it presents and should therefore be considerably shortened (below the general length limit)
Summary of paper in a few sentences (summary of changes and improvements for
second round reviews):
The paper tackles the problem of assessing the “FAIRness” of research data, and presents a semi-automatic pipeline to FAIR maturity indicators. The pipeline is demonstrated in a Jupyter notebook and illustrated in two use cases in the domain of Life Sciences. The proposed pipeline follows the principles and guidelines recommended by the maturity indicator authoring group in addition to integrate concepts from the state of the art. Specifically, they proposed pipeline satisfies 13 FAIR principles, and allows for the retrieval of data collection by accessing different data repositories. The metadata describing the process of data collection retrieval is documented in XML. The effectiveness of the proposed pipeline is evaluated in two use cases and the results of the evaluation are illustrated in a FAIR ballon plot. This plot facilitates the visualization of the analysis of the FAIR maturity indicators during the process of data collection retrieval to answer scientific questions. Finally, two users are consulted to analyze usability of proposed pipeline.
Reasons to accept:
-) A resource for evaluating the FAIRness of the data collections retrieved during the execution of a research question.
-) Live code of the pipeline accessible via a Jupyter notebook.
-) A clear visualization of the summary of the values of the results?
Reasons to reject:
-) The components of the pipeline are vaguely defined. It is not clear what is the innovation of the proposed workflow from a computational point of view
This is the second submission of the paper where the authors have included some new material with the aim of addressing the reviewers' comments. Albeit including more detailed explanations, the paper still lacks a clear and precise description of the components of the proposed workflow. In that sense, I consider that my comments have not been fully addressed in this new version of the work and my recommendation to the authors is to prepare an abstract description of the proposed framework in order to understand the innovations of this framework from the computational point of view.