عنوان مقاله [English]
Objective: Data-driven research is an emerging paradigm that has led to the need for effective and accurate management of research data. Research data needs to be stored, maintained using appropriate methods to make it easy to discover, retrieve and reuse them in order to create added value. Accordingly, it is important to manage the research data that organizes the data, from entering the research cycle to publishing and sharing that data, recording and maintaining valuable research results. The purpose of this article is to identify and analyze the standard and applied dimensions of research data management implemented in the world of scientific and research environments.
Methods: This is a systematic review with a qualitative approach that aims at expanding and emphasizing the methods of providing research data management services in universities and research centers, using MAXQDA10 software to analyze the content of scientific resources and documents. With qualitative approach and utilization of content analysis method using MAXQDA 10 software, this research has examined scientific and research resources and documents in the field of research data management. For this purpose, first, with the open coding method, the concepts were extracted from the texts, and then with the central coding and searching for the commonalities of the concepts, finally the final concepts were extracted. Accordingly, the process of gathering documents using the library method and searching for credible scientific databases has continued until the theoretical saturation point and dimensions and components have been replicated.
Results The Analysis of the literature revealed that 403 concepts were extracted using MAXQDA 10 software. In addition to the topic of research data management, these concepts include the areas of research data sharing, their benefits, challenges and solutions. Given the wide range of concepts in the aforementioned areas, this study emphasizes the 321 concepts extracted in terms of implementing research data management system in universities and scientific centers.The research showed that the implementation of the research data management system in universities and science centers depends on five essential components: policy, planning, services, stakeholders, and technology, each of which has a wide range of dimensions and processes. Understanding the needs, being aware of the challenges, developing the knowledge and skills needed will help to formulate policies and planning appropriately to make the best use of data management services and networks available today, in most universities and research centers.
Conclusion: : Finally, it can be concluded that with regard to the limited research on the management of research data in Iranian Universities and Research Centers, each of the categories presented in the present study highlights the new dimensions and methods in this field. Iranian universities and research centers are also expected to either individually or in coalition for the necessary policies and planning to implement the National Research Data Management Services System.