Location
Expo Center
Session Number
4
Description
Many international, national, and institutional principles and policies as well as a growing number of funders and publishers recommend or mandate researchers to write data management plans (DMPs) or share the underlying research data upon which the research articles are based. At the core of these alignments is to enhance research transparency, reproducibility and reliability, and the reuse of research data by bringing the data findable, accessible, interoperable, and reusable (FAIR). To help researchers fulfill this task, they need education in research data management (RDM).
The goal of this preliminary paper is to find out the quality of the DMPs developed by doctoral students (DSs) in a 10-week, 3 ECTS credits multi-stakeholder Basics of Research Data Management (BRDM) course. Moreover, we aim to identify differences between DMPs in relation to background variables such as year, discipline, course track or other variables. The course is held in two multi-faculty research-intensive universities in Finland since 2019. In this ongoing study, 130 DSs’ DMPs have been assessed and rated from 2020 and 2021 so far, using the criteria of the Finnish DMP Evaluation Guide (FDEG).
The quality of the DMPs appeared to be satisfactory. The differences between DMPs developed in separate years, course tracks or disciplines were statistically insignificant. However, DMPs that contained a data type specific classification (a data table) differed statistically highly significantly from DMPs without a data table. DMPs with a data table acknowledged better than DMPs without a data table the data handling needs of different data types and improved the overall quality of a DMP.
DMPs illustrated how well DSs had learned RDM competencies and how the course had furthered comprehension of the importance of sound data management practices to the integrity and reliability of the research, to the reusability of data, and to the reproducibility of the research.
Included in
Doctoral Students’ Research Data Management Competencies Based on the Quality of Their Data Management Plans
Expo Center
Many international, national, and institutional principles and policies as well as a growing number of funders and publishers recommend or mandate researchers to write data management plans (DMPs) or share the underlying research data upon which the research articles are based. At the core of these alignments is to enhance research transparency, reproducibility and reliability, and the reuse of research data by bringing the data findable, accessible, interoperable, and reusable (FAIR). To help researchers fulfill this task, they need education in research data management (RDM).
The goal of this preliminary paper is to find out the quality of the DMPs developed by doctoral students (DSs) in a 10-week, 3 ECTS credits multi-stakeholder Basics of Research Data Management (BRDM) course. Moreover, we aim to identify differences between DMPs in relation to background variables such as year, discipline, course track or other variables. The course is held in two multi-faculty research-intensive universities in Finland since 2019. In this ongoing study, 130 DSs’ DMPs have been assessed and rated from 2020 and 2021 so far, using the criteria of the Finnish DMP Evaluation Guide (FDEG).
The quality of the DMPs appeared to be satisfactory. The differences between DMPs developed in separate years, course tracks or disciplines were statistically insignificant. However, DMPs that contained a data type specific classification (a data table) differed statistically highly significantly from DMPs without a data table. DMPs with a data table acknowledged better than DMPs without a data table the data handling needs of different data types and improved the overall quality of a DMP.
DMPs illustrated how well DSs had learned RDM competencies and how the course had furthered comprehension of the importance of sound data management practices to the integrity and reliability of the research, to the reusability of data, and to the reproducibility of the research.