Plankton are organisms that in essence drift in the oceans. They range from microbial organisms to jelly fish and krill. Plankton have played a key role in planetary ecosphere functioning (having produced half of the atmospheric oxygen that we breath, and also most of the limestone and much of the non-coal fossil fuels). They continue to play an important role in climate change events, food sustainability (fisheries), down to local societal levels in harmful algal blooms and sea-snot (beach foam) events. This project will provide the foundation for pivotal developments in marine science, namely configuring plankton for the digital twins of the oceans. Digital twins (DTs) are computer-based analogues for real systems; well-known examples are flight simulators and many reality-based video game platforms. DTs are heavily used in engineering and in business, providing design and testing platforms. They are especially useful for 'what-if?' testing. However, it is critical that the end user has trust that the platform they are using does indeed describe a digital twin that would be deemed satisfactory to experts in the real system. This work comprises essential underpinning for the UK and international initiatives to produce within this decade digital twins of oceanic processes of societal importance, including the United Nations Digital Twins of the Oceans (DITTO) initiative. The idea behind DITTO, for example, is to see the generation of DT platforms, freely available to the public with a suitable graphic-user-interface, to support education, management and decision making. Some of these may be within game-like platforms to engage and inform the public about plankton (why their local beach is out-of-bounds due to harmful algal bloom or jelly-fish, for example), while other platforms will support science policy and management. Despite the critical importance of plankton in marine ecology, the current generation of computer descriptions ('models') provides only a poor caricature of the real organisms that is quite unsuitable for digital twin applications. The reasons for this include a lack of suitable data to directly support modelling, and a hitherto poor interaction between modelers and those empiricists who study real plankton. The project will work by exploiting 'expert witness validation', an approach similar to that of the famous Turing test for artificial intelligence, which aims to produce models that are sufficiently realistic in their behaviour that experts in the subject (plankton) cannot tell the difference. The project will work with experts in each plankton group to reach a consensus on what computer models of different plankton types should behave like such that they could be considered as a 'digital twin'. The one-year project will see the production of reference-type materials (such as check-lists, and example response patterns) to guide future development of plankton models, specifically for digital twin applications to ensure that the description of these organisms accords with the expectations of experts in the field.