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The team at GEOMAR and NOC is working on making marine image data FAIR (Findable, Accessible, Interoperable, and Reusable) using image FAIR Digital Objects (iFDOs). They provide a standardised framework for processing marine imagery. The team further presents an infrastructure environment to create, validate, manage, and store these iFDOs, and which data associated with imagery should be curated (see figure below).
The goal is to reduce image management overheads while simultaneously creating visibility for image acquisition and publication efforts. Ultimately, the curated image data are the key to efficient and effective Artificial Intelligence (AI) applications that detect and classify objects within well-curated image data sets.
Underwater images are used to explore and monitor ocean habitats, generating huge datasets with unusual data characteristics that preclude traditional data management strategies. Due to the lack of universally adopted (meta)data standards, image data collected from the marine environment are increasing in heterogeneity, thus preventing objective comparison. Hence, the extraction of actionable information remains challenging, particularly for researchers not directly involved with the image data collection. Standardised formats and procedures following the FAIR principles, such as the iFDOs, are needed to enable sustainable image analysis and processing tools, as are solutions for image publication in long-term repositories to ascertain reuse of data.
If you want more info, do not hesitate to contact Timm Schoening (tschoening[at]geomar.de), but please also check the following:
Main contributors: Timm Schoening, Jennifer Durden, Henk-Jan Hoving, based at the GEOMAR Helmholtz Centre for Ocean Research (Germany) and the National Oceanography Centre (UK)