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Project Members:

Graham Galloway (NIF Lead)

Andrew Mehnert (National Project Manager, UWA Lead, andrew.mehnert@uwa.edu.au)

Marco Gruwel (UNSW Lead, c.power@unsw.edu.au)

Wojtek James Goscinski (Monash Lead, Wojtek.goscinski@monash.edu)

Andrew Janke (UQ Lead)

ANDS Contact:

Andrew Treloar (andrew.treloar@ands.org.au)

Project Status:

In Progress

NIF: UQ, UWA, UNSW and Monash - Delivering durable, reliable, high-quality image data

National Imaging Facility

Collaborator(s): University of Queensland, University of Western Australia, University of New South Wales and Monash University

Project Description

This project is co-funded with Research Data Services.

The projects aims to (1) develop and demonstrate a list of requirements that are necessary and sufficient to obtain trusted data from NIF instruments (i.e. to ensure the quality, durability and reliability of data acquired on NIF instruments) and (2) to manage that trusted data in a trustworthy way.

For researchers, the outcomes will include:
● Improved integration with international activity
● Higher quality data to contribute to, and engage in, international collaborations
● Analysis/pre-processing will be performed using predefined workflows on a managed platform. Results will include provenance of which versions of software were used or that they have been abstracted from, for example, a particular version of the CVL.

For research institutions, the outcomes will include:
● Ability to reliably deliver trusted data to researchers and partners
● Harvested data will include reference to recent automated quality control (QC) results relevant to the particular instrument and scan protocol performed. Weekly/monthly QC may involve automated verification runs.
For the research system, the outcomes will include:
● Improved evidential quality of data from research facilities
● Network of trusted data repositories, compatible with evolving European Open Science Cloud approach
● Automated data harvest from scanners to repositories. This reduces human interaction with data; increasing quality and reliability