Data Curation: Introducing a Competency Framework for the Social Sciences
Research data management includes more than the question how researchers handle their data. In the sense of the FAIR principles, it is also about the sustainable safeguarding and organized reusability of research data. For social science, data-intensive research, research data centers and their data...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
University of Edinburgh
2025-06-01
|
| Series: | International Journal of Digital Curation |
| Online Access: | https://ijdc.net/index.php/ijdc/article/view/889 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849468158948147200 |
|---|---|
| author | Kathrin Behrens Tatiana Kvetnaya |
| author_facet | Kathrin Behrens Tatiana Kvetnaya |
| author_sort | Kathrin Behrens |
| collection | DOAJ |
| description | Research data management includes more than the question how researchers handle their data. In the sense of the FAIR principles, it is also about the sustainable safeguarding and organized reusability of research data. For social science, data-intensive research, research data centers and their data curating staff are therefore becoming increasingly important: data curators usually take on curation-specific tasks such as data preparation, securing research data in suitable archival environments, ensuring data accessibility, and the related control of the conditions of data re-use by third parties. Hence, they are specialized in the entire data curation process and, in particular, take on tasks of archiving and providing research data for reuse. Although the standards of comprehensive research data management are becoming more and more specific, this trend has not yet arrived in the corresponding training and further education measures. As a result, there is a gap between the growing demands on data curators and the development of competencies in the field of research data management with a focus on data curation. The competency framework presented in this article is intended to help close this gap: based on a Data Curation Lifecycle Model, a competency framework has been developed to support the development of targeted training and continuing education programs in the field of data curation, the formulation of learning objectives, and the evaluation of the corresponding trainings. The article points out the necessity to advance the development of competencies for this field, illustrates the schematic substructure of the data curation lifecycle, describes the development as well as the central core elements of the presented competency framework and discusses its perspectives. Overall, this competence framework is aimed in particular at (future) data curators, or as a schematic basis for the training of the relevant personnel. The focus is primarily on the data-intensive discipline of social sciences, although large parts can certainly be adapted for other disciplines and the corresponding data curation. The competency framework and this companion article are thereby intended to assist in advancing the sustainable professionalization of the previously understudied competency field of data curation.
|
| format | Article |
| id | doaj-art-5dbfddfbbe2d459b96b558f3cee0b2c2 |
| institution | Kabale University |
| issn | 1746-8256 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | University of Edinburgh |
| record_format | Article |
| series | International Journal of Digital Curation |
| spelling | doaj-art-5dbfddfbbe2d459b96b558f3cee0b2c22025-08-20T03:25:56ZengUniversity of EdinburghInternational Journal of Digital Curation1746-82562025-06-0119110.2218/ijdc.v19i1.889Data Curation: Introducing a Competency Framework for the Social SciencesKathrin Behrens0https://orcid.org/0000-0003-1191-5110Tatiana Kvetnaya1https://orcid.org/0000-0002-5477-1199GESIS - Leibniz Institute for the Social SciencesGoethe University FrankfurtResearch data management includes more than the question how researchers handle their data. In the sense of the FAIR principles, it is also about the sustainable safeguarding and organized reusability of research data. For social science, data-intensive research, research data centers and their data curating staff are therefore becoming increasingly important: data curators usually take on curation-specific tasks such as data preparation, securing research data in suitable archival environments, ensuring data accessibility, and the related control of the conditions of data re-use by third parties. Hence, they are specialized in the entire data curation process and, in particular, take on tasks of archiving and providing research data for reuse. Although the standards of comprehensive research data management are becoming more and more specific, this trend has not yet arrived in the corresponding training and further education measures. As a result, there is a gap between the growing demands on data curators and the development of competencies in the field of research data management with a focus on data curation. The competency framework presented in this article is intended to help close this gap: based on a Data Curation Lifecycle Model, a competency framework has been developed to support the development of targeted training and continuing education programs in the field of data curation, the formulation of learning objectives, and the evaluation of the corresponding trainings. The article points out the necessity to advance the development of competencies for this field, illustrates the schematic substructure of the data curation lifecycle, describes the development as well as the central core elements of the presented competency framework and discusses its perspectives. Overall, this competence framework is aimed in particular at (future) data curators, or as a schematic basis for the training of the relevant personnel. The focus is primarily on the data-intensive discipline of social sciences, although large parts can certainly be adapted for other disciplines and the corresponding data curation. The competency framework and this companion article are thereby intended to assist in advancing the sustainable professionalization of the previously understudied competency field of data curation. https://ijdc.net/index.php/ijdc/article/view/889 |
| spellingShingle | Kathrin Behrens Tatiana Kvetnaya Data Curation: Introducing a Competency Framework for the Social Sciences International Journal of Digital Curation |
| title | Data Curation: Introducing a Competency Framework for the Social Sciences |
| title_full | Data Curation: Introducing a Competency Framework for the Social Sciences |
| title_fullStr | Data Curation: Introducing a Competency Framework for the Social Sciences |
| title_full_unstemmed | Data Curation: Introducing a Competency Framework for the Social Sciences |
| title_short | Data Curation: Introducing a Competency Framework for the Social Sciences |
| title_sort | data curation introducing a competency framework for the social sciences |
| url | https://ijdc.net/index.php/ijdc/article/view/889 |
| work_keys_str_mv | AT kathrinbehrens datacurationintroducingacompetencyframeworkforthesocialsciences AT tatianakvetnaya datacurationintroducingacompetencyframeworkforthesocialsciences |