z-logo
open-access-imgOpen Access
Key components of data publishing: Using current best practices to develop a reference model for data publishing
Author(s) -
Claire C. Austin,
Theodora Bloom,
Sünje Dallmeier-Tiessen,
Varsha Khodiyar,
Fiona Murphy,
Amy Nurnberger,
Lisa Raymond,
Martina Stockhause,
Jonathan Tedds,
Mary Vardigan,
Angus Whyte
Publication year - 2015
Publication title -
zenodo (cern european organization for nuclear research)
Language(s) - English
DOI - 10.5281/zenodo.34542
Subject(s) - publishing , key (lock) , computer science , data publishing , current (fluid) , data science , political science , engineering , computer security , electrical engineering , law
Additional Contributors:Tim Clark, Eleni Castro, Elizabeth Newbold, Samuel Moore, Brian HoleThis is the revised version of: Bloom, Theodora et al.. (2015). Workflows for Research Data Publishing: Models and Key Components (Submitted Version). Zenodo. 10.5281/zenodo.20308AbstractPurpose:Availability of workflows for data publishing could have an enormous impact on researchers, research practices and publishing paradigms, as well as on funding strategies and career and research evaluations. We present the generic components of such workflows in order to provide a reference model for these stakeholders.Methods:The RDA-WDS Data Publishing Workflows group set out to study the current data publishing workflow landscape across disciplines and institutions. A diverse set of workflows were examined to identify common components and standard practices, including basic self-publishing services, institutional data repositories, long term projects, curated data repositories, and joint data journal and repository arrangements. Results:The results of this examination have been used to derive a data publishing reference model comprised of generic components. From an assessment of the current data publishing landscape, we highlight important gaps and challenges to consider, especially when dealing with more complex workflows and their integration into wider community frameworks. Conclusions:It is clear that the data publishing landscape is varied and dynamic, and that there are important gaps and challenges. The different components of a data publishing system need to work, to the greatest extent possible, in a seamless and integrated way. We therefore advocate the implementation of existing standards for repositories and all parts of the data publishing process, and the development of new standards where necessary. Effective and trustworthy data publishing should be embedded in documented workflows. As more research communities seek to publish the data associated with their research, they can build on one or more of the components identified in this reference model

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here