Primary users: Users interested in reusing the data or the underlying method to manage other fisheries data in the same way: researchers (fisheries scientists, ocean modelliers), data scientists, data managers, fisheries policy-makers.

Secondary users: SMEs exploiting the infrastructure and services to develop new services on top, and Industry that collaborates with management authorities to ensure sustainable fisheries management; Academia

Tertiary users: general public, data journalism, NGOs looking for information about sustainability of marine species / food safety

• Maintenance of the core SDI OS components (Geonetwork, geoserver etc)
• Improvements to bespoke SDI components such as GEOFLOW to better manage dataflows into and out of the system
• Improve support to time dimension and regional atlases
• Analytical capacity for geostatistics and time series
• Computing capacity for ecological modelling

End products of the Fisheries Atlas are meant to be reproducible since we generate time series of fisheries data. The main goal of our work is to ensure our ability to easily run a yearly update of our time series by relying on a stable infrastructure. GRSF is a product per se – doesn’t need replicability.

At least till middle of 2028, while extension to 2030 is very likely, since CNR is continuing to manage and operate the underlying D4Science e-infrastructure, and there are bilateral arrangements between CNR and FAO. The results depend on data availability which is managed by the FIRMS partnership to ensure a long-term collaboration between tuna RFMOs, FAO and IRD. FAO re-uses many components, bringing down the costs of maintenance and on-boarding similar services. For what concerns the GRSF, operation and maintenance of the service is secured thanks to a great global collaboration with leaders in academia and industry.

What needs to be funded to continue the service?

● The underlying infrastructure to ensure reproducibility of the work within a stable a runtime environment

● ETP engineers to improve the quality of existing code and datasets and to create new products, and to reproduce the work of previous projects even if no projects is bringing funding.