Big Data Platform for Smart Aquaculture
Step 3: Visioning workshop
The visioning step brings key stakeholders together to agree on the platform’s objectives, governance principles, and data-sharing rules. Participatory methods such as value chain mapping and systems diagrams help build shared understanding. An important early check is whether a suitable platform or component already exists and could be adapted rather than built from scratch.
The visioning process should result in agreement on the key characteristics the platform must have.
An effective Big Data Platform for Smart Aquaculture should be:
- Valuable to users. The intended functions and services of the platform should be clarified. These may include biosecurity and disease surveillance, water quality monitoring, environmental risk assessment, climate early warning systems, production optimization, traceability, food safety monitoring, market intelligence, or integrated decision-support services. The selected functions will determine the types of data that must be collected, the infrastructure required, the governance arrangements needed, and the level of analytical capacity that must be developed.
- Inclusive. Designed to serve all production intensities, from small-scale extensive producers to large commercial intensive farms, with appropriate interfaces and services for each.
- Interoperable. Built on open standards (OGC SensorThings API, DCAT, ISO 19115, FAIR data principles) to ensure compatibility with national government systems and international data networks.
- Scalable. Capable of expanding to accommodate more sensors, users, farms, and analytical services over time without requiring a full system rebuild.
- Secure and privacy-respecting. Role-based access controls ensure that commercially sensitive farm data is not exposed to competitors, while aggregate and anonymized data can be shared for public benefit.
- Governed. Clear data ownership, data-sharing agreements, and accountability mechanisms (e.g. designated data stewards in each participating institution) are essential.
- Sustainable. The platform must have a viable business model or funding mechanism for long-term operation, maintenance, and upgrading.
- Risk-aware. Compliant with relevant AI governance frameworks (NIST AI Risk Management Framework, ISO 42001, EU AI Act or equivalent national frameworks) to ensure AI/ML methods are validated, transparent, and safe.
Use the checklist below to verify that all key elements of this step have been addressed or refer to the overall checklist to ensure all recommended actions are planned or completed: