@article {67241, title = {A perspective on Microscopy Metadata: data provenance and quality control}, journal = {arXiv}, year = {2021}, month = {2021 Apr 26}, abstract = {

The application of microscopy in biomedical research has come a long way since Antonie van Leeuwenhoek discovered unicellular organisms. Countless innovations have positioned light microscopy as a cornerstone of modern biology and a method of choice for connecting omics datasets to their biological and clinical correlates. Still, regardless of how convincing published imaging data looks, it does not always convey meaningful information about the conditions in which it was acquired, processed, and analyzed. Adequate record-keeping, reporting, and quality control are therefore essential to ensure experimental rigor and data fidelity, allow experiments to be reproducibly repeated, and promote the proper evaluation, interpretation, comparison, and re-use. To this end, microscopy images should be accompanied by complete descriptions detailing experimental procedures, biological samples, microscope hardware specifications, image acquisition parameters, and image analysis procedures, as well as metrics accounting for instrument performance and calibration. However, universal, community-accepted Microscopy Metadata standards and reporting specifications that would result in Findable Accessible Interoperable and Reproducible (FAIR) microscopy data have not yet been established. To understand this shortcoming and to propose a way forward, here we provide an overview of the nature of microscopy metadata and its importance for fostering data quality, reproducibility, scientific rigor, and sharing value in light microscopy. The proposal for tiered Microscopy Metadata Specifications that extend the OME Data Model put forth by the 4D Nucleome Initiative and by Bioimaging North America [1-3] as well as a suite of three complementary and interoperable tools are being developed to facilitate the process of image data documentation and are presented in related manuscripts [4-6].

}, url = {https://arxiv.org/abs/1910.11370}, author = {Maximiliaan Huisman and Mathias Hammer and Alex Rigano and Ulrike Boehm and James J. Chambers and Nathalie Gaudreault and Alison J. North and Jaime A. Pimentel and Damir Sudar and Peter Bajcsy and Claire M. Brown and Alexander D. Corbett and Orestis Faklaris and Judith Lacoste and Alex Laude and Glyn Nelson and Roland Nitschke and David Grunwald and Caterina Strambio-De-Castillia} } @article {67242, title = {Towards community-driven metadata standards for light microscopy: tiered specifications extending the OME model.}, journal = {bioRxiv}, year = {2021}, month = {2021 Apr 28}, abstract = {

Digital light microscopy provides powerful tools for quantitatively probing the real-time dynamics of subcellular structures. While the power of modern microscopy techniques is undeniable, rigorous record-keeping and quality control are required to ensure that imaging data may be properly interpreted\ (quality),\ reproduced\ (reproducibility),\ and used to extract reliable information and scientific knowledge which can be shared for further analysis (value). Keeping notes on microscopy experiments and quality control procedures ought to be straightforward, as the microscope is a machine whose components are defined and the performance measurable. Nevertheless, to this date, no universally adopted community-driven specifications exist that delineate the required information about the microscope hardware and acquisition settings (i.e., microscopy {\textquotedblleft}data provenance{\textquotedblright} metadata) and the minimally accepted calibration metrics (i.e., microscopy quality control metadata) that should be automatically recorded by both commercial microscope manufacturers and customized microscope developers. In the absence of agreed guidelines, it is inherently difficult for scientists to create comprehensive records of imaging experiments and ensure the quality of resulting image data or for manufacturers to incorporate standardized reporting and performance metrics. To add to the confusion, microscopy experiments vary greatly in aim and complexity, ranging from purely descriptive work to complex, quantitative and even sub-resolution studies that require more detailed reporting and quality control measures.

}, doi = {10.1101/2021.04.25.441198v1}, url = {https://www.biorxiv.org/content/10.1101/2021.04.25.441198v1}, author = {Mathias Hammer and Maximiliaan Huisman and Alex Rigano and Ulrike Boehm and James J. Chambers and Nathalie Gaudreault and Alison J. North and Jaime A. Pimentel and Damir Sudar and Peter Bajcsy and Claire M. Brown and Alexander D. Corbett and Orestis Faklaris and Judith Lacoste and Alex Laude and Glyn Nelson and Roland Nitschke and Farzin Farzam and Carlas S. Smith and David Grunwald and Caterina Strambio-De-Castillia} }