Preparing and organising datasets
NCI has a team of expert data managers who work with, organise, and curate the datasets for optimal accessibility, analysis and data publication and accessibility. Our approach for data management falls into a process of making data fit-for-purpose for computation and programmatic access, and in the context of organising data in the context of a variety of funded schemes. This team works closely with data depositors to develop their Data Management Plan that will inform how datasets are catalogued, published, data capacity and managed over time on NCI. This also prepares the information for how the datasets are supported and paid for (e.g., through NCRIS, agency or university funding).
Roles and responsibilities
NCI is responsible for the quality of the data repository and all its functions and internal consistency of all the information. The following Roles and Responsibilities have been established:
Data Collections are managed by NCI to agreed community and international standards that strongly relate the data to both transdisciplinary use as well as domain specific needs. NCI leads the process of broader consultation through community management as resolved through the NCI Allocation Committee, its Scientific Assessment Panel and Technical Advisory Group;
NCI is responsible for the organisation and coordinated activities of data within the collections, in concert with Dataset Managers and Organisational staff such as Data Stewards. This includes development of Data Management Plans (DMPs) and ensuring datasets comply with NCI’s Data Quality Strategy (link to Informatics - and Open Access Journal);
To ensure uniformity in the stakeholder communication and management of the service, NCI is responsible for communications about changes to data areas. The content of advice will be developed in consultation with data providers. It is therefore important that any updates within data areas is managed under controlled procedures;
- To enable and curate the datasets to be used for modern data analysis, cutting edge methods, inputs to computational models. Our computational and data science activities are part of our Specialised Environments; and
- To meet current and emerging requirements for data citation within Journals and other scientific-based publications and processes. These include national activities such as NCRIS and ARC, and international activities such as large-scale climate analysis.
The value of any data at NCI is considered at the Data Collection and SubCollection level, including funding arrangements for the storage allocations for each of the underlying data Subcollections.
Help with accessing or managing datasets
If you represent a university, federal or state government science or institution, NCRIS capability that generates, owns or requires access to big data, contact us at help@nci.org.au to find out how we can help you.