Background
Integration of knowledge and models from specialized fields is essential for improving fish farming planning and operations. The end results of an aquaculture production cycle in terms of product properties, quality and economy depend on many different factors as illustrated below.

Project goals
The project started early this year, and the overall objective is to develop a framework for simulation, optimization and monitoring of all aspects of modern fish farming. To limit the complexity, the scope of the initial framework is floating fish farms. Main goals for 2009 are:

• Use selected cases/application areas to identify functional specifications and to identify relevant technical components/tools the framework should include
• Demonstrate the feasibility of the framework by prototyping the framework and integrating models for selected cases
• Describe roadmap for further development

The project has R&D challenges along several directions:

• Establishing common platforms for data capture, ontology, knowledge representation etc. across multiple disciplines
• Integration of heterogeneous model environments
• Data synchronization and performance issues
• HMI design and evaluation

Figure 1 Simulation and optimization of planning and operations requires modeling tools and access to on-line and historical data. The framework will facilitate the integration of both existing models and models developed in CREATE.

It is also expected that the work on the CREATE platform will identify lack of knowledge or models within some disciplines. This implies that the platform needs to be dynamic, i.e. support continuous development and exchange of components as the industry evolves. One focus area in the initial project phase is the development of use cases for future application areas.