An integrated Conceptual Framework to Harness Artificial Intelligence for Enhanced Data Management in Context
| dc.contributor.author | Mosha, Neema | |
| dc.contributor.author | Ngulube, Patrick | |
| dc.date.accessioned | 2026-01-19T05:45:34Z | |
| dc.date.issued | 2026-01-31 | |
| dc.description | SDG-4: Quality Education SDG-9: Industry, Innovation and Infrastructure | |
| dc.description.abstract | This study explores the transformative impact of artificial intelligence (AI) technologies on research data management (RDM) services in higher learning institutions (HLIs), with a specific focus on the roles played by academic libraries. It highlights how these libraries strategically incorporate AI to enhance RDM effectiveness and stewardship. An integrated conceptual framework is proposed, which includes AI tools, RDM services, the functions of academic libraries, necessary support structures, and the challenges related to AI and RDM in HLIs. The findings indicate that this framework can significantly boost the efficiency of AI adoption, leading to streamlined workflows and reduced time for RDM services such as data generation, processing, storage, access, and reuse. Additionally, the framework supports the development of innovative AI technologies tailored to library users, including research management software, data security and quality assurance, and metadata generation. | |
| dc.identifier.uri | https://doi.org/10.55267/iadt | |
| dc.identifier.uri | https://dspace.nm-aist.ac.tz/handle/123456789/3634 | |
| dc.language.iso | en | |
| dc.publisher | Journal of Information Systems Engineering and Management | |
| dc.subject | Artificial Intelligence (AI) | |
| dc.subject | Data stewardship | |
| dc.subject | Innovative technologies | |
| dc.subject | Ethical guidelines | |
| dc.subject | Metadata generation | |
| dc.subject | Data security | |
| dc.title | An integrated Conceptual Framework to Harness Artificial Intelligence for Enhanced Data Management in Context | |
| dc.type | Article |