RMIT s Digital Research Infrastructure Roadmap:Towards A Strategic Approach in Research Excellence
In response to the rapid evolution of digital technologies, RMIT has recognised the necessity of a robust digital research infrastructure (DRI) to drive research excellence. To stay at the forefront of this digital revolution, RMIT has adopted an institutional approach to formulate a DRI roadmap. The primary aim of our DRI roadmap is to strategically enhance our research capabilities and foster innovation, by leveraging international, national and institutional DRI infrastructure. Specifically, our roadmap focuses on five key pillars: 1.Data: We aim to provide secure, scalable, and user-friendly research data storage solutions across the institution, promoting research excellence and ensuring our data is FAIR and CARE compatible. 2.Computing: Recognising the essential role of robust computing resources in accelerating the journey from data to knowledge or new discoveries, we aim to equip researchers at RMIT and beyond with scalable cloud and high-performance computing infrastructure. 3.Training: To fully leverage DRI resources, our roadmap includes regular training and workshops to empower both existing and prospective researchers with essential digital skills. 4.Software and Platforms: Our DRI roadmap aims to maintain essential software and platforms to boost research productivity. 5.Emerging Technologies: To stay competitive, our DRI roadmap will proactively explore and potentially adopt cutting-edge technologies such as AI, quantum computing, and cyber-physical systems. Developing a comprehensive DRI roadmap is a strategic approach in RMIT s future. This presentation will highlight the benefits for researchers and our institution, and share the lessons learned from implementing the initial DRI roadmap initiatives.
Institutions
- MIT University (MK)
- RMIT University (AU)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2024-10-30
- DOI
- https://doi.org/10.5281/zenodo.15293445
- Primary Topic
- Scientific Computing and Data Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00