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The five tuna Regional Fishery Management Organizations (tRFMOs) are responsible for collating, analysing and disseminating fisheries data from their member countries required for stock assessment, management, and enforcement of management measures. These datasets generally include catch, effort, and size data covering large spatial scales over several decades. These rich datasets are also very complex, heterogenous, and include some large uncertainties, e.g. in reporting small-scale fisheries. In addition, data structures differ between the tRFMOs, and similar information across tRFMOs may be expressed by using different formats, labels, units, and granularity. These factors make interbasin comparisons difficult, and they can lead to misunderstandings of tuna fisheries. Recent projects have aimed to harmonise the semantics of tRFMO data in terms of concepts and terminology (e.g. code lists), improve communication, and promote greater transparency and accessibility to their datasets (i.e., GEF funded Common Oceans ABNJ Tuna project, 1,2). These projects were driven by the need to improve data quality and availability in order to address key questions on monitoring and management of tuna fisheries (e.g. monitoring of the global fishing capacity) and ecology such as habitat preferences and the impacts of climate change (Lewison et al. 2004, Reygondeau et al. 2012, Arrizabalaga et al. 2015, Dueri et al.
2016, Monllor-Hurtado et al. 2017). These datasets can also be a valuable source of information for data-poor assessment approaches (e.g. catch time series collapse, changes in mean trophic level of catch). There is a global call for increased data quality and harmonisation between national, regional and global statistics such that the collation of fisheries statistics is systematic and transparent across all levels. Increasingly, the streamlining of data flows among agencies is being encouraged (ABNJ, CWP), and data sharing arrangements are being promoted among FAO and RFBs. The Coordinating Working Party (CWP) on Fishery Statistics Task Group was established to develop a global standard for Reference Harmonization.
