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The RDA community is invited to comment on a variety of documents while they undergo a community review phase as part of their endorsement or recognition by RDA. These documents include:

  • Working Group (WG) Case Statements and Interest Group (IG) Charters that outline the scope and expected outputs of a group at the start of the group’s life.
  • RDA Recommendations, the official, endorsed results of RDA WGs and RDA’s flagship outputs. They are adoptable results, e.g. specific tools, code, best practices, or standards that will promote data sharing and exchange and increase data-driven innovation.
  • RDA Supporting Outputs, useful solutions produced by RDA WGs or IGs.
  • Other documents produced by RDA task forces or other RDA initiatives

Usually, those documents stay open for community review for a month. They are listed in the "RfC box" on the home page.

Below you can find a list of the documents currently under community review.



Research Hardware Definition

FAIR Principles for Research Hardware IG Group Co-chairs: Nadica Miljković, Julien Colomb Subgroup Chair: Alexander Struck Supporting Output Title: Research Hardware Definition

Comment: 0

FAIRification of Genomic Annotations WG Case Statement

Motivation: Since the completion of the Human Genome Project, we have witnessed an explosion of datasets annotating particular locations along reference DNA sequences with e.g. aspects of functional processes. Tremendous amounts of research funding have been provided to large and small projects that have generated genomic annotation datasets. Many of these datasets relate to human genomes, but an increasing amount of such data is also generated for other model organisms – and with the recent surge of biodiversity projects – for a range of species spanning the whole tree of life. Unfortunately, researchers who want to make use of such data face practical challenges in discovering and reusing datasets relevant to their research. While many repositories and data distribution solutions exist, the metadata is often poorly aligned with best practices for Findable, Accessible, Interoperable and Reusable (FAIR) research data. Even in cases where proper metadata exists, relevant solutions typically provide metadata according to different metadata models and APIs.

Comment: 0