RDA/WDS Publishing Data Workflows WG Recommendations

  RDA/WDS Publishing Data Workflows WG

Recommendation Title: Workflows for Research Data Publishing: Models and Key Components

Impact: Assists research communities in understanding options for data publishing workflows and increases awareness of emerging standards and best practices. Partnership with the Data Seal of Approval (DSA) and the ICSU World Data System (ICSU­WDS)

Recommendation package DOI: http://dx.doi.org/10.15497/RDA00004

Group Chair:

Sünje Dallmeier-Tiessen, CERN
Fiona Murphy, Wiley
Varsha Khodiyar, Scientific Data
Amy Nurnberger, Columbia University
Theodora Bloom, BMJ


Workflows that enable persistence, quality control and access are all crucial to enhance the possibilities for greater discoverability as well as efficient and reliable reuse of research data. Such workflows for data publishing are at the core of this analysis and working group. 
Final paper: DOI Dataset: DOI


Endorsed. RDA DOI: http://dx.doi.org/10.15497/RDA00004

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  • Mustapha Mokrane's picture

    Author: Mustapha Mokrane

    Date: 02 Nov, 2016

    The final paper: Key components of data publishing: using current best practices to develop a reference model for data publishing can be found here: https://zenodo.org/record/56789. This should be updated.

  • Elizabeth Griffin's picture

    Author: Elizabeth Griffin

    Date: 02 Mar, 2017

    Dear Chair(s),

    Your document speaks plenty about "publishing data", but does not specify which "data" are being meant.  From what I can glean, it is using the same word for input (original) data, derived information, and deduced knowledge.  This is muddling in the extreme.  The three should never be mixed in the way suggested, for the very reason that they are separate entities and physical separation is the simplest way of illustrating *and teaching* that that is the case.  The very fact that "numerous research groups" have approved the document is itself evidence that most others have not thought this through sufficiently clearly, but that they are assuming everyone else can guess which "data" word means what.  Please attend to this issue - it is something that is growing worse nowadays because all of the younger generation coming into science speak of "data" from the get-go, and without much clarity of what they are referring to.

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