Reporting and reproducibility in microscopy

Guidelines for improving reporting and reproduciblity in microscopy take center stage in this month’s Focus issue.

Sharing, teaching and singing to bring people together on microscopy standards.

Comprehensive guidelines and resources to enable accurate reporting for the most common fluorescence light microscopy modalities are reported with the goal of improving microscopy reporting, rigor and reproducibility.

Bioimaging data have significant potential for reuse, but unlocking this potential requires systematic archiving of data and metadata in public databases. We propose draft metadata guidelines to begin addressing the needs of diverse communities within light and electron microscopy. We hope this publication and the proposed Recommended Metadata for Biological Images (REMBI) will stimulate discussions about their implementation and future extension.

The community-driven initiative Quality Assessment and Reproducibility for Instruments & Images in Light Microscopy (QUAREP-LiMi) wants to improve reproducibility for light microscopy image data through quality control (QC) management of instruments and images. It aims for a common set of QC guidelines for hardware calibration and image acquisition, management and analysis.

Rigorous record-keeping and quality control are required to ensure the quality, reproducibility and value of imaging data. The 4DN Initiative and BINA here propose light Microscopy Metadata Specifications that extend the OME Data Model, scale with experimental intent and complexity, and make it possible for scientists to create comprehensive records of imaging experiments.

Imaging technologies are used throughout the life and biomedical sciences to understand mechanisms in biology and diagnosis and therapy in animal and human medicine. We present criteria for globally applicable guidelines for open image data tools and resources for the rapidly developing fields of biological and biomedical imaging.

Micro-Meta App is an intuitive, highly interoperable, open-source software tool designed to facilitate the extraction and collection of relevant microscopy metadata as specified by recent community guidelines.

OME’s next-generation file format (OME-NGFF) provides a cloud-native complement to OME-TIFF and HDF5 for storing and accessing bioimaging data at scale and works toward the goal of findable, accessible, interoperable and reusable bioimaging data.