Challenges of reusing marine image-based data for fish and benthic habitat Essential Variables: insights from data producers

Dominique Pelletier^1*Jacquomo Monk²Franziska Althaus³Catherine Borremans⁴Melissa HANAFI PORTIER^4,5Ben Scoulding³Karine Olu⁴Candice Bobby Untiedt³Chris James Jackett³Neville Scott Barrett²Pascal Laffargue⁶Sandrine Vaz⁷Elisabeth Hasan¹Alan Williams³

• ¹UMR DECOD, IFREMER, Institut Agro, INRAE, Lorient, France
• ²University of Tasmania Institute for Marine and Antarctic Studies, Hobart, Australia
• ³CSIRO Environment, Hobart, Australia
• ⁴UMR BEEP, IFREMER, Université de Bretagne Occidentale, CNRS, Plouzané, France
• ⁵CNRS, Sorbonne Université, Ecole Pratique des Hautes Etudes, Université des Antilles, UMR ISYEB, Muséum National d'Histoire Naturelle, Paris, France
• ⁶UMR DECOD, Ifremer, Institut Agro, INRAE, Nantes, France
• ⁷UMR MARBEC, Univ. Montpellier, CNRS, Ifremer, IRD, Sète, France

Understanding the status and trends of Essential Ocean Variables (EOV) and Essential Biodiversity Variables (EBV) is crucial for informing policy-makers and the public about sustainable management of marine biodiversity. Marine image data hold significant potential in this context, offering a permanent, information-rich and non-extractive record of marine environments at the time of capture. Quantitative image-based measurements such as species abundance and distribution have proven to be highly effective for engaging diverse stakeholders. The exchange and reuse by experienced fisheries scientists and marine ecologists of nine image-based datasets (including images, metadata and annotations) collected through various protocols revealed a substantial disconnect between initial expectations and actual practical usability, particularly in terms of understanding and reusing data. Two key issues were highlighted. First, the link between the datasets and their potential applications in deriving EOV/EBV was often inadequately described or absent. Second, despite both initial and ongoing efforts to document the data, new users continued to face challenges in understanding underlying properties and contextual features of datasets. We suggest these findings are likely to characterise many, if not most, historical image-based datasets. While standards promoting the FAIR principles (Findable, Accessible, Interoperable, and Reusable) for image-based data are emerging, our focus here is on the specific features of documentation that enable or facilitate reuse of data for the purpose of deriving EOV/EBV. From this perspective, we provide a set of recommendations for documenting both images and their associated annotations, aimed at supporting broader applications of in situ image data in marine conservation and ecology.