RDA Professionalising Data Stewardship - Data Stewardship Landscape Initial Report
Professionalising Data Stewardship IG |
Group co-chairs: Peter Neish, Romain DAVID, Debora Drucker, Christina Drummond, Yan Wang, Niklas Zimmer, Graham Parton, Jaana Pinnick |
Supporting Output title: RDA Professionalising Data Stewardship - Data Stewardship Landscape Initial Report |
Authors: Lorna Wildgaard, Jukka Rantasaari Editors: Claudia Engelhardt, Jaana Pinnick |
Impact: The main take-home messages from this review are: 1) Collaborate internationally on certified training; 2) Enable researchers to share their data from the planning stage of their project and 3) Address the increased need for technical skills in data stewardship. The report offers 197 solutions compiled from literature to bridge gaps in data stewardship. The output can be used to identify and recommend learning pathways for data stewards, and to identify use cases to concretize the solutions in order to provide a valuable tool for data stewards. The results of the report could be used to contribute to the Competency Hub pages on Data Stewardship, the continuing work of the EOSC Taskforce or the creation of new educational materials for RDA task group developing curricula. The report will also give valuable information to all who are interested in developing their data stewardship skills needed to better serve the needs of researchers. |
DOI: 10.15497/RDA00076 |
Citation: Wildgaard, L., & Rantasaari, J. (2022). RDA Professionalising Data Stewardship - Data Stewardship Landscape Initial Report. Research Data Alliance. https://doi.org/10.15497/RDA00076 |
Abstract
This report is based on a literature review published by the Research Data Alliance Professionalising Data Stewardship Interest Group (RDA PDS-IG) Training sub-group in October 2022. A framework for the literature collection was devised before the literature search began, based on common concepts of the division of the research disciplines. The literature search was conducted between March 2021 and July 2021. The selection was verified in a cross-walk exercise, where common terminologies were tracked across different ontologies to learn more about concepts and disciplinary differences and commonalities in research data management (RDM). In the reference management software Zotero, folders were created to structure the literature into the following categories: data stewardship; education and training of data stewards; RDM education; training materials; data management plan templates; documents about the skills needed to support EOSC and FAIR principles; data management in the humanities, industry, life sciences, natural sciences, public institutions and the social sciences. Further, the aim was to identify papers concerning the RDM needs of researchers and data stewards and their role in the RDM life cycle. The screening resulted in 125 papers that are used as the knowledge base for this report.
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Author: Yuri Demchenko
Date: 29 Nov, 2022
The report misses reference to and corresponding analysisn of at least two results o the FAIRsFAIR project:
1) Deliverable D7.3 that proposed the Data Stewardship Professional Competence Framework
"D7.3 FAIR Competence Framework for Higher Education (Data Stewardship Professional Competence Framework)" - https://zenodo.org/record/4562089#.Y4VXiHbMK38
The deliverable uses evidence based identification of important Data Stewards competences, skills and knowledge based on the job market analysis.
2) Deliverable D7.4 "How to be FAIR with your data. A teaching and training handbook for higher education institutions" https://zenodo.org/record/6674301#.Y4VaZnbMK38
and
3) Book "How to be FAIR with your data: A teaching and training handbook for higher education institutions", by Claudia Engelhardt et al. Published 2022, DOI: https://doi.org/10.17875/gup2022-1915,
Other related resources
4) Data Steward Professional: Reference dataset of Data Steward related job vacancies for competences assessment
https://zenodo.org/record/6008122#.Y4VYg3bMK38
5) Research Data Management and Data Stewardship Competences in University Curriculum
Yuri Demchenko; Lennart Stoy
Proc. EDUCON2021 – IEEE Global Engineering Education Conference (EDUCON2021), Vienna, Austria (Virtual), 21-23 April 2021 (Session Session "Special Session Data Science Education")
https://zenodo.org/record/4633752#.Y4VYp3bMK38
6) EDISON Data Science Framework (EDSF) that defined Data Steward professional profile (back in 2017) and related documents CF-DS, DS-BoK, MC-DS, DSPP
https://edisoncommunity.github.io/EDSF/
Author: Jaana Pinnick
Date: 01 Dec, 2022
Thank you for reading our draft outputs and taking the time to provide comments on them. We have considered the feedback and here is our reply:
We hope this addresses the points you queried but we're happy to provide further information if needed.
Author: Jaana Pinnick
Date: 01 Dec, 2022
Thank you for reading our draft outputs and taking the time to provide comments on them. We have considered the feedback and here is our reply:
We hope this addresses the points you queried but we're happy to provide further information if needed.