GNS Science is committed to meeting its obligations to manage science data well, as outlined in the New Zealand Data and Information Management Principles.
We apply FAIR Principles in our approach to best practise digital data management. These principles, being Findable, Accessible, Interoperable and Reusable are being assessed for our high-value geoscience datasets.
Twenty-seven of these datasets are grouped within our eight Nationally Significant Collections and Databases. They span geological maps, paleontology, rocks and minerals, volcanoes, earthquakes, groundwater and geomagnetism. For comparison, we have also assessed four other data resources covering landslides, active faults, tsunami and geodesy. These contain a further 23 natural hazard datasets.
GNS Science’s Dataset Catalogue is a critical metadata information resource that enables good FAIR compliance. The catalogue’s metadata can be searched, including through external search engines and data registries, and this ensures our data are Findable. The catalogue describes the Interoperable and Reusable components of the data and points to where our data are Accessible from.
Each dataset has been assessed in terms of its FAIR compliance by adapting a quantitative tool, which was developed in Australia and is based on international criteria.
The Nationally Significant Collections and Databases datasets score highly in the Findable, Accessible and Reusable principles; many are also scoring well for their Interoperable status. The high-value natural hazard datasets also score highly under Findable but generally lower in terms of the other components.
The higher FAIR scores for the Nationally Significant Collections and Databases datasets reflect the consistent levels of funding directed towards their information management.
The quantitative FAIR compliance analysis method we have applied is globally significant; we described our method to an international forum of geological surveys information managers in June and this has helped spur a work programme around consistent measurement of FAIR compliance of geoscientific data across geological surveys.
The analysis we undertook was time-intensive and involved a discussion with each dataset manager. Through undertaking the analysis, our dataset managers better understood the principles of good data management for their dataset and for the wider organisational framework. We were also able to make improvements to many metadata records that significantly improved FAIR scores.
The detailed FAIR Principles report is available from GNS Science.
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