Scientific research, and in particular preclinical research, produces a huge amount of imaging data, but the current lack of procedures and programs for their annotation and archiving constitutes a significant limit to their availability and reuse [1]. For this reason, the development of procedures for the annotation of biomedical images and for the use of ontologies for a correct description are of fundamental importance [2]. These aspects fall within the definition of the FAIR principles (Findable, Accessible, Interoperable, Reusable [3]) that the various scientific imaging communities, both biological and medical, are slowly adopting to facilitate the sharing and reuse of the imaging data produced.

The aim of this work is to develop procedures and tools that facilitate i) the description and annotation of preclinical image datasets, ii) the selection of ontologies that allow easier queries and iii) the development of a repository to facilitate their reuse.

In particular, a list of metadata useful for describing in detail the preclinical image datasets, taking into account their multidisciplinary nature, was defined. For these metadata, 15 ontologies were identified and selected, covering several fields/domains, including the ontology describing the condition of (re)use of the data produced (DUO). Tools were also developed to allow the annotation of biomedical images, their transfer to the XNAT platform to facilitate their sharing and reuse and for quality control assessment. A repository for the metadata describing the PIDAR preclinical images (https://pidar.hpc4ai.unito.it/ ) was also developed to make these datasets findable following a keyword-based query. Overall, these tools will improve the FAIRification of preclinical image datasets.

Acknowledgements

References

[1] Schmidt C, Hanne J, Moore J, Meesters C, Ferrando-May E, Weidtkamp-Peters S; members of the NFDI4BIOIMAGE initiative. Research data management for bioimaging: the 2021 NFDI4BIOIMAGE community survey. F1000Res. 2022 Jun 10;11:638.

[2] Kemmer I, Keppler A, Serrano-Solano B, Rybina A, Özdemir B, Bischof J, El Ghadraoui A, Eriksson JE, Mathur A. Building a FAIR image data ecosystem for microscopy communities. Histochem Cell Biol. 2023 Sep;160(3):199-209.

[3] Wilkinson MD, Dumontier M, Aalbersberg IJ et al; The FAIR Guiding Principles for scientific data management and stewardship. Sci Data. 2016 Mar 15;3:160018

Conflict of Interest

I or one of my co-authors have no financial interest or relationship to disclose regarding the subject matter of this presentation.