Abstract: Policies responding to increasing pressures on marine biodiversity require adequate data to support their implementation and to monitor their effectiveness. Marine biodiversity science has made significant progress generating and aggregating biodiversity data, however turning this into evidence-based knowledge useful to decision makers remains a significant challenge. 'Data products' provide processed data to address specific user needs, and are widely used in climate science, geosciences, and remote sensing, but the development of biodiversity data products is challenging due to the complexity of biological systems and of the data derived from surveys designed without explicit biodiversity policy or management guidance. A wide range of potential products of interest may include distributional data for thousands of individual taxa, requiring advanced statistical methods to model patterns in biodiversity using heterogeneous and sparse source data with biases in spatial, temporal, and taxonomic coverage. We illustrate these challenges using data products created within the Biology thematic lot of the European Marine Observation and Data Network (EMODnet), and we propose that the EMODnet Biology approach, which involves providing clear and open documentation of the product creation process with a strong emphasis on the computational tools needed to link source data to higher-level data products, can productively support decision making at the European scale. Furthermore, this approach provides part of the essential infrastructure required to maximise the financial benefits of FAIR data, and data products play a key role in empowering users to make maximum use of existing biodiversity data to help to understand and manage our seas.

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