Librarian's Perception of RDM-Data.sav

<b>Librarians' Perceptions of Research Data Management: A Dataset on Awareness and AI Integration</b>This dataset explores librarians' perceptions of Research Data Management (RDM), with a specific focus on their awareness and knowledge of artificial intelligence (AI) applications in RDM practices. The study examines various dimensions of RDM, including data planning, collection, documentation, storage, security, sharing, and long-term preservation. It further assesses librarians' familiarity with AI-driven tools that enhance RDM efficiency.The data was gathered through a structured questionnaire distributed to librarians across the institutions. Respondents provided insights into their level of awareness of RDM and their understanding of AI tools applicable to different RDM stages. The questionnaire contained both demographic questions and Likert-scale items measuring agreement levels (Strongly Disagree to Strongly Agree).<b>Variables used in the data</b><b>Demographic Information:</b> library affiliation, gender, academic qualification, years of experience, and job rank.<b>RDM Awareness:</b> Understanding of RDM principles, data management planning, documentation, security, sharing, and preservation.<b>AI Knowledge in RDM:</b> Familiarity with AI applications in automating metadata generation, improving data security, enhancing discoverability, and optimizing data storage and preservation.<b>Data Processing and Analysis</b>Responses were coded and analysed using SPSS Version 28. A descriptive statistical technique was applied to identify the level of awareness of RDM and AI adoption among librarians.<b>Ethical Considerations</b>Participation was voluntary, and all responses were anonymized to maintain confidentiality.<br>