Developing research data management (RDM) services has become an international trend in response to the movement promoting open science. There is an urgent need to establish support systems for universities and research institutions to strengthen governance. However, the diversity of RDM services and the absence of a universally applicable model create challenges in implementation. To address this, we propose a maturity model for organizational RDM services. By analyzing existing RDM service maturity models, we extract six key dimensions —awareness, data policy, budget, services, user needs, and IT infrastructure—and develop a structured evaluation framework with a five-level rating system. The model is validated through a step-by-step approach: author evaluation, domain evaluation, and practical setting evaluation via a national survey of Japanese institutions. The results demonstrate the model’s applicability across institutions of varying sizes and types, enabling RDM managers to quantitatively assess service maturity and compare progress against national benchmarks. Furthermore, we discuss the potential value and utilization of the framework through two case studies. This study provides an organizational benchmark for RDM services that is applicable to institutions of diverse sizes and natures. It also helps identify issues in the future implementation of organizational RDM services and highlights priority areas for investment.
https://doi.org/10.5334/dsj-2025-018
| Artificial Intelligence |
| Research Data Curation and Management Works |
| Digital Curation and Digital Preservation Works |
| Open Access Works |
| Digital Scholarship |
