The FAIR Guiding Principles for scientific data management and stewardship

[wavingtowaves]

Title: The FAIR Guiding Principles for scientific data management and stewardship

Study Link: https://www.doi.org/10.1038/sdata.2016.18
Citation: @doi:10.1038/sdata.2016.18

Suggested keywords that help identify the relevance of this paper to Ecology and Evolution:

• FAIR data
• data management
• data standards
• sharing data

Which areas of expertise are particularly relevant to the paper?

• ecology and/or evolution;
• biostatistics;
• informatics and computational research;
• open science and reproducibility;

Summary

• This is first publication of FAIR principles.
• Moves from peer to peer type of responsibility model to one where there's an emphasis of machine readability and reusability.
• Provides nice definitions for key terms including DOI, RDF and interoperability.
  special purpose vs. general purpose repositories.
  The data that go into general purpose datasets are no less essential for making sure they are interoperable and reusable.
  However, little restriction on type of data that goes into general purpose and even less checking to see if the data are interoperable.
  Examples of FAIR principles in action and the benefits to interoperability. (Wilkinson et al. 2016)

Suggested questions to answer about each paper:

• What is the general main finding or takeaway of the paper?
• What did they analyze and how did they do it?
• What does this paper suggest to improve the issue with reproducibility in science?
• Do you have any concerns about methodology or the interpretation of these results beyond this analysis?

Any comments or notes?