Identifying the Dimensions of the Development of Research Data Management Services in Scientific Centers

Objective: Data-driven research, given the hidden and vital value of research data, is an emerging paradigm that has led to the need for effective and proper management of research data. Research data needs to be stored and retrieved using appropriate methods to make it easy to discover, retrieve, and reuse to add value. Accordingly, it is important to manage research data that includes the organization of data, from entering the research cycle to publishing and sharing that data, recording and maintaining valuable research results. The aim of this study is to identify the dimensions of research data management development by emphasizing the methods of providing research data management services that have been implemented in scientific and research environments around the world. Methodology: This research is a systematic review with a qualitative approach to identify the dimensions of research data management development, using MAXQDA10 software to analyze the content of scientific resources and documents. Accordingly, the process of collecting documents using the library method and searching for scientific databases has continued to reaching the point of theoretical saturation and the repetition of dimensions and components. Also, in order to ensure that the theoretical saturation point is reached and the validity of the research are guaranteed, the websites of the top ten universities in the world in the field of research activities in 2019 were observed. With the open coding method, the concepts were extracted from the texts, and then with the central coding and searching for the commonality of the concepts, the graph of the categories was drawn. In total, 403 concepts were extracted from the collected documents, of which 321 concepts are in the field of research data management and 82 concepts are related to the areas of research data sharing, advantages, challenges and solutions. Then, it was ensured that basic concepts in research data management were identified. Findings: It is apparent that the implementation of research data management in universities and scientific centers depends on five basic components: politics, planning, services, stakeholders and technology, which each have a wide range of dimensions and multiple processes. Understanding needs, being aware of existing challenges, developing the necessary knowledge and skills will help determine appropriate policies and planning to best use existing networks and technical infrastructure, which are now available to most universities and research centers, to provide data management services. Conclusion: In this research, while presenting the basic categories of research data management, dimensions and new methods in the field have been clearly identified. It is expected that Iranian universities and research centers will also work integrated to implement new policies and programs needed to provide and develop research data management services to prevent redundancies and additional costs in the research process