UTS Strategic Direction
The UTS vision is to be a world-leading university of technology – we will do this by embedding and showcasing leading edge IT and other technologies in all disciplines[…]
The goal of the 2016-2020 UTS Research Strategy is to increase the intensity, excellence, impact and reputation of our research to position UTS clearly within the top 10 Australian universities and the top 10 in chosen fields globally by 2020
The eResearch Strategy outlines how UTS will organise, prioritise and invest in eResearch infrastructure, services and support to raise researcher capability and productivity.
Success criteria for the UTS eResearch Strategy:
- Researchers and their students have access to best in class research infrastructure consistent with a world-leading university of technology
- UTS is seen as a leader in research data management, with mature practices and systems for capturing, managing, sharing and reusing research data
- IT systems support researchers, not vice versa
eResearch Program Roadmap
The goal for 2020 is to have an active catalogue of services, integrating both internal and external services with built in provisioning covering:
- Data management: storage, Data Management Planning (DMP), dataset management, publishing, archiving preservation
- Compute: High performance Computing) HPC and mid-range computing as well as hosted apps and services
- Applications: Virtual labs, research software, license servers
- Support: Continued high level eResearch consulting and support
- Training: An active research skills training program
eResearch Sourcing Principles
Default to international, national and/or regional facilities where available.
Proactively engage as an early adopter, to ensure facilities are fit for purpose for UTS – but continue to invest selectively in UTS services where there is a clear user requirement that cannot otherwise be met, or where these can complement external services
Default to open.
Open source, open formats, open standards, open data, open licenses and open knowledge preferred
Leverage economies of scale.
eResearch will use standard UTS hardware and sourcing, except where specialised technologies are necessary (e.g. fast storage for High Performance Computing (HPC))
Invest in immutable infrastructure.
Commissioning of servers, compute stacks and other services should be automated using orchestration and deployment tools across different environments
Maintain multi-modal HPC expertise.
'Cloud-only' cannot meet all requirements: there are still researchers who need HPC collocated with dedicated network and storage
High-performance computing as an application.
Encourage and explore pathways away from specialised, dedicated hardware to applications which run on commodity hardware or cloud.
Research Data Management Principles
Researchers are ultimately responsible for research data management (RMD).
By supporting researchers to manage data effectively, UTS increases the integrity and impact of our research.
Storage is not data management.
For mature research data management and for research data storage to be sustainable, we need end to end data management services across the research life cycle.
Research data security is critically important.
Risks around research data use and disclosure need to be managed appropriately.
Data is appropriately accessible.
ALL research data must be Findable and Accessible for Integrity of Research (FAIR). MOST research data should be Findable, Accessible, Interoperable and Re-usable, ideally on national or global research infrastructure, and as openly available as possible given ethical, commercial and competitive constraints.
Use linked open data principles, common vocabularies and data definitions.
Common vocabularies and standards should be used wherever possible.
Encourage reproducible research via managed pipelines.
Research pipelines can be captured and orchestrated with modern software orchestration tools and systems.