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  • Private Initiative
  • National
  • Federation
Last updated: 2021-10-20 08:39

Strategic Goals

These projects goals is to establish industry standards for communication and storage of data produced by these 3 business areas in the industry.

Solutions Developed / Used

Aquacloud 2.0 will develop guidelines and protocols for data and exchange of data built on open standards that enables communication and analysis across company borders.


Start Date 01/01/2017
Project Focus
  • Regulator
Geographical Scope
  • National
  • Federation
Cloud Delivery Model
  • SaaS
Cloud Deployment Model
  • Public
Project Life-Cycle Stage
  • Research and Innovation
  • Agriculture
Specific Domains Targeted
  • Green Deal
  • Artificial Intelligence / Machine Learning
  • Big Data


    Academic/Research Organisations
  • Norway
    The Institute of Marine Research (Norway)
  • Industry
  • Norway
    Grieg Seafood (Norway)
  • United States of America
    IBM (USA) (United States of America)
  • Norway
    Lerøy Seafood Group (Norway)
  • Norway
    Mowi (Norway)
  • Norway
    SalMar (Norway)
  • Community Organisations
  • Norway
    Seafood Innovation Cluster (Norway)

⭐ Good Practice Description

Aquacloud is an innovation initiative from the Norwegian aquaculture sector that collects and consolidates data sets from different aquaculture companies to solve a shared problem – predicting and preventing the outbreak of sea lice. Aquacloud includes good practices related to organizational structure and data governance.

Success Factors

Governance and Organizational Structure

The initiative is running on specific project funding at the moment, and the long-term structure has not yet been decided. The plan is to move to a commercial model that will make Aquacloud self-sustainable, but it will remain a non-profit organization. Aquacloud is governed by a steering committee from the participating companies.

Data Governance

Aquacloud has built a central repository for data that integrates the production systems of aquaculture companies. Improving data quality has also emerged as a success criterion, as well as identifying next steps and widening the stakeholder group to achieve networking effects and drive the adoption of data standards.

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