@article {67305, title = {Micro-Meta App: an interactive software tool to facilitate the collection of microscopy metadata based on community-driven specifications}, journal = {bioRxiv}, year = {2021}, month = {2021 May 31}, abstract = {

For the information content of microscopy images to be appropriately interpreted, reproduced, and meet FAIR (Findable Accessible Interoperable and Reusable) principles, they should be accompanied by detailed descriptions of microscope hardware, image acquisition settings, image pixel and dimensional structure, and instrument performance. Nonetheless, the thorough documentation of imaging experiments is significantly impaired by the lack of community-sanctioned easy-to-use software tools to facilitate the extraction and collection of relevant microscopy metadata. Here we present\ Micro-Meta App, an intuitive open-source software designed to tackle these issues that was developed in the context of nascent global bioimaging community organizations, including\ BioImaging\ North\ America (BINA) and\ QUAlity Assessment and\ REProducibility in\ Light\ Microscopy (QUAREP-LiMi), whose goal is to improve reproducibility, data quality and sharing value for imaging experiments. The App provides a user-friendly interface for building comprehensive descriptions of the conditions utilized to produce individual microscopy datasets as specified by the recently proposed 4DN-BINA-OME tiered-system of Microscopy Metadata model. To achieve this goal the App provides a visual guide for a microscope-user to: 1) interactively build diagrammatic representations of hardware configurations of given microscopes that can be easily reused and shared with colleagues needing to document similar instruments. 2) Automatically extracts relevant metadata from image files and facilitates the collection of missing image acquisition settings and calibration metrics associated with a given experiment. 3) Output all collected Microscopy Metadata to interoperable files that can be used for documenting imaging experiments and shared with the community. In addition to significantly lowering the burden of quality assurance, the visual nature of Micro-Meta App makes it particularly suited for training users that have limited knowledge of the intricacies of light microscopy experiments. To ensure wide-adoption by microscope-users with different needs Micro-Meta App closely interoperates with\ MethodsJ2\ and\ OMERO.mde, two complementary tools described in parallel manuscripts.

}, author = {Alex Rigano and Shannon Ehmsen and Serkan Utku Ozturk and Joel Ryan and Alexander Balashov and Mathias Hammer and Koray Kirli and Karl Bellve and Ulrike Boehm and Claire M. Brown and James J. Chambers and Robert A. Coleman and Andrea Cosolo and Orestis Faklaris and Kevin Fogarty and Thomas Guilbert and Anna B. Hamacher and Michelle S. Itano and Daniel P. Keeley and Susanne Kunis and Judith Lacoste and Alex Laude and Willa Ma and Marco Marcello and Paula Montero-Llopis and Glyn Nelson and Roland Nitschke and Jaime A. Pimentel and Stefanie Weidtkamp-Peters and Peter J. Park and Burak Alver and David Grunwald and Caterina Strambio-De-Castillia} } @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} }