The Most Effective Indicators and Components in Research Data Management Literacy

Document Type : Original Article

Authors
Mozhgan Oroji 1
Najla Hariri 2
Fahimeh Babalhavaeji 3
1 PhD., Department of Information Science and Knowledge, Science and Research Branch, Islamic Azad University, Tehran, Iran
2 Prof., Department of Communication Science and Knowledge, Science and Research Branch, Islamic Azad University, Tehran, Iran
3 Associate Prof., Department of Communication Science and Knowledge, Science and Research Branch, Islamic Azad University, Tehran, Iran
10.22034/aimj.2024.481928.1606
Abstract
The present research identifies the components and indicators of research data management literacy. In this research, a qualitative approach has been used using the meta-composite method and in the next step, the Delphi method. After preparing a comprehensive list of available documents in the field of research data management literacy, relevant keywords were searched in scientific databases inside and outside of Iran, and then the components of research data management were identified. The second stage was refined and validated using a researcher-made questionnaire in two rounds of Delphi among Delphi panel members. Six main categories were found in the process of identifying the components of research data management: 1- beneficiaries, 2- services, 3- politics, 4- types of literacy, 5- data, 6- budget and after implementation. The opinion of experts added 2 other categories: 1- types of participation and 2- monitoring. Also, 10 new concepts were identified, which were approved by experts. The identified codes were also 50 codes related to research data management literacy. The results showed that the six main identified categories explain 60% of the total variance of the variables. Each of which includes related concepts and codes and appropriate criteria for measurement. It is important to know how practical the development, acceptance and application of these categories can be in conducting research data management methods.

Keywords

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Iranian Journal of Information Management
Volume 9, Issue 1 - Serial Number 16
September 2024
Pages 77-96

  • Receive Date 05 October 2024
  • Revise Date 08 December 2024
  • Accept Date 21 December 2024