Open Science Principles#

Motivation#

The advantages of good data management for NOAA's mission, including machine readability and compliance with US Government mandates.

Why manage data#

The FAIR data principles were defined in the 2016 Scientific Data paper The FAIR Guiding Principles for scientific data management and stewardship and are listed here. The criteria of the FAIR principles are as follows:

  • Findable – Data/metadata should be richly described, include the identifier of the data they describe, be assigned a globally unique and persistent identifier, and be indexed in a searchable resource.
  • Accessible – Data/metadata should be retrievable by an identifier using a standardized communications protocol, which is open, free, and universally implementable, and the metadata should be accessible even when the data are no longer available.
  • Interoperable – Data/metadata should use a formal, accessible, shared, and broadly applicable language for knowledge representation, using vocabularies that follow FAIR principles, and include qualified references to other metadata and/or data.
  • Reusable – Data/metadata are richly described with a plurality of accurate and relevant attributes, are released with a clear and accessible data usage license, are associated with detailed provenance, and meet domain-relevant community standards.


Useful Resources for FAIRification#

Findable & Accessible#

How to find NOAA and other data, and how to make your data findable (keywords, persistent identifiers, cross-listing)#

  • List of keywords to include with 'Omics studies: [add controlled Omics vocab list here]
  • Register for an ORCiD, which links all of your research works to a persistent and unique identifier.
  • Cross-list publications and other research material on platforms like ResearchGate and Biorxiv
  • Utilize DOIs or accession numbers whenever cross-listing data, metadata, code, and publications. Do not only include a URL!


Standard language for publications#

All raw sequence files associated with this study can be found in the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) under BioProject PRJN####. Environmental and sample metadata is available at NCEI [accession number here]. Processed datasets and analysis scripts generated from this study are available in a Github repository [insert URL here] with the Zenodo DOI [insert DOI here].


Interoperable & Reusable#

Licenses#

Understand the licenses associated with data when submitted to repositories, and include an appropriate license with provided code. [include boilerplate license required for federal employees. Make recommendation for license for other users]


Machine readability#


Government mandates#