@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 {66009, title = {QUAREP-LiMi: A community-driven initiative to establish guidelines for quality assessment and reproducibility for instruments and images in light microscopy}, journal = {Journal of Microscopy}, volume = {284}, year = {2021}, month = {2021 Oct 01}, pages = {56-73}, abstract = {

In April 2020, the QUality Assessment and REProducibility for Instruments and Images in Light Microscopy (QUAREP-LiMi) initiative was formed. This initiative comprises imaging scientists from academia and industry who share a common interest in achieving a better understanding of the performance and limitations of microscopes and improved quality control (QC) in light microscopy. The ultimate goal of the QUAREP-LiMi initiative is to establish a set of common QC standards, guidelines, metadata models, and tools, including detailed protocols, with the ultimate aim of improving reproducible advances in scientific research. This White Paper 1) summarizes the major obstacles identified in the field that motivated the launch of the QUAREP-LiMi initiative; 2) identifies the urgent need to address these obstacles in a grassroots manner, through a community of stakeholders including, researchers, imaging scientists, bioimage analysts, bioimage informatics developers, corporate partners, funding agencies, standards organizations, scientific publishers, and observers of such; 3) outlines the current actions of the QUAREP-LiMi initiative, and 4) proposes future steps that can be taken to improve the dissemination and acceptance of the proposed guidelines to manage QC. To summarize, the principal goal of the QUAREP-LiMi initiative is to improve the overall quality and reproducibility of light microscope image data by introducing broadly accepted standard practices and accurately captured image data metrics.

}, url = {https://arxiv.org/abs/2101.09153}, author = {Glyn Nelson and Ulrike Boehm and Steve Bagley and Peter Bajcsy and Johanna Bischof and Claire M Brown and Aurelien Dauphin and Ian M Dobbie and John E Eriksson and Orestis Faklaris and Julia Fernandez-Rodriguez and Alexia Ferrand and Ali Gheisari and Hella Hartmann and Christian Kukat and Alex Laude and Miso Mitkovski and Sebastian Munck and Alison J North and Tobias M Rasse and Ute Resch-Genger and Lucas C Schuetz and Arne Seitz and Caterina Strambio-De-Castillia and Jason R Swedlow and Ioannis Alexopoulos and Karin Aumayr and Sergiy Avilov and Gert-Jan Bakker and Rodrigo R Bammann and Andrea Bassi and Hannes Beckert and Sebastian Beer and Yury Belyaev and Jakob Bierwagen and Konstantin A Birngruber and Manel Bosch and Juergen Breitlow and Lisa A Cameron and Joe Chalfoun and James J Chambers and Chieh-Li Chen and Eduardo Conde-Sousa and Alexander D Corbett and Fabrice P Cordelieres and Elaine Del Nery and Ralf Dietzel and Frank Eismann and Elnaz Fazeli and Andreas Felscher and Hans Fried and Nathalie Gaudreault and Wah Ing Goh and Thomas Guilbert and Roland Hadleigh and Peter Hemmerich and Gerhard A Holst and Michelle S Itano and Claudia B Jaffe and Helena K Jambor and Stuart C Jarvis and Antje Keppler and David Kirchenbuechler and Marcel Kirchner and Norio Kobayashi and Gabriel Krens and Susanne Kunis and Judith Lacoste and Marco Marcell and Gabriel G Martins and Daniel J Metcalf and Claire A Mitchell and Joshua Moore and Tobias Mueller and Michael S Nelson and Stephen Ogg and Shuichi Onami and Alexandra L Palmer and Perrine Paul-Gilloteaux and Jaime A Pimentel and Laure Plantard and Santosh Podder and Elton Rexhepaj and Arnaud Royon and Markku A Saari and Damien Schapman and Vincent Schoonderwoert and Britta Schroth-Diez and Stanley Schwartz and Michael Shaw and Martin Spitaler and Martin T Stoeckl and Damir Sudar and Jeremie Teillon and Stefan Terjung and Roland Thuenauer and Christian D Wilms and Graham D Wright and Roland Nitschke and Laurent Gelman} } @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} }