Sprecher
Beschreibung
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 data standards, image data collected from the marine environment are increasing
in heterogeneity, preventing objective comparison. the extraction of actionable information thus
remains challenging, particularly for researchers not directly involved with the image data collection.
Standardized formats and procedures 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.
the FaIR principles (Findable, accessible, Interoperable, Reusable) provide a framework for such
data management goals. We propose the use of image FaIR Digital Objects (iFDOs) and present an
infrastructure environment to create and exploit such FaIR digital objects. We show how these iFDOs
can be created, validated, managed and stored, and which data associated with imagery should be
curated. the goal is to reduce image management overheads while simultaneously creating visibility for
image acquisition and publication efforts.
