High-resolution digital microscopy provides ever more powerful tools for probing the real-time dynamics of subcellular structures, and adequate record-keeping is necessary to evaluate results, share data , and allow experiments to be repeated. In addition to advances in microscopic techniques, post-acquisition procedures such as image-data processing and analysis (i.e., feature counting, distance measurements, intensity comparison , and colocalization studies) are often required for the reproducible and quantitative interpretation of images. While these techniques increase the usefulness of microscopy data, the limits to which quantitative resultsmay be interpreted are often poorly quantified and documented. Keeping notes on microscopy experiments and calibration procedures should be relatively unchallenging, as the microscope is a machine whose performance should be easy to assess. Nevertheless, to this date, no widely adopted data provenance and quality control metadata guidelines to be recorded or published with imaging data exist. Metadata automatically recorded by microscopes from different companies vary widely and pose a substantial challenge for microscope users to create a good faith record of their work.Similarly, the complexity and aim of experiments using microscopes vary, leading to different reporting and quality control requirements from the simple description of a sample to the need to document the complexities of sub-diffraction resolution imaging in living cells and beyond. To solve this problem, the 4DN Imaging Standards Working Group has put forth a tiered system of microscopy calibration and metadata standards for images obtained through fluorescence microscopy. The proposal is an extension of the OME data model and aims at increasing data fidelity, ease future analysis, and facilitate objective comparison of different datasets, experimental setups, and essays .
The application of microscopy in biomedical research has come a long way since Antonie van Leeuwenhoek discovery of URLanisms through his hand-crafted microscope. Countless innovations have propelled imaging techniques and have positioned fluorescence microscopy as a cornerstone of modern biology and as a method of choice for connecting omics datasets to their biological and clinical correlates. Still, regardless of how convincing imaging results look, they do not always convey meaningful information about the conditions in which they were acquired, processed and analyzed to achieve the presented results. Adequate record-keeping and quality control are therefore essential to ensure experimental rigor and data fidelity, to allow experiments to be reproducibly repeated and to promote the proper evaluation, interpretation, comparison and re-use of the results. Microscopy images must be accompanied by complete descriptions of experimental procedures, biological samples, microscope hardware specifications, image acquisition parameters, and metrics detailing instrument performance and calibration. Despite considerable effort (Goldberg et al., 2005; Linkert et al., 2010), however, universal data standards and reporting guidelines for the fair (Wilkinson et al., 2016) assessment and comparison of microscopy data have not been established. To understand this discrepancy and propose a way forward, we examine the benefits, pitfalls, and limitations of shared standards for fluorescence microscopy .
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High-resolution digital microscopy provides ever more powerful tools for probing the real-time dynamics of subcellular structures, and adequate
The application of microscopy in biomedical research has come a long way since Antonie van Leeuwenhoek discovery of URLanisms through his hand-crafted microscope. Countless innovations have propelled imaging techniques and have positioned fluorescence microscopy as a cornerstone of modern biology and as a method of choice for connecting omics datasets to their biological and clinical correlates. Still, regardless of how convincing imaging results look, they do not always convey meaningful information about the conditions in which they were acquired, processed and analyzed to achieve the presented results. Adequate
R
is necessary to evaluate results, share data , and
and quality control are therefore essential to ensure experimental rigor and data fidelity, to
R
repeated. In addition to advances in microscopic techniques, post-acquisition procedures such as image-data processing and analysis (i.e., feature counting, distance measurements, intensity comparison , and colocalization studies) are often required for the reproducible and quantitative interpretation of images. While these techniques increase the usefulness of microscopy data, the limits to which quantitative resultsmay be interpreted are often poorly quantified and documented. Keeping notes on microscopy experiments and calibration procedures should be relatively unchallenging, as the microscope is a machine whose performance should be easy to assess. Nevertheless, to this date, no widely adopted data provenance and quality control metadata guidelines to be recorded or published with imaging data exist. Metadata automatically recorded by microscopes from different companies vary widely and pose a substantial challenge for microscope users to create a good faith record of their work.Similarly, the complexity and aim of experiments using microscopes vary, leading to different reporting and quality control requirements from the simple description of a sample to the need to document the complexities of sub-diffraction resolution imaging in living cells and beyond. To solve this problem,
reproducibly repeated and to promote the proper evaluation, interpretation, comparison and re-use of
R
4DN Imaging Standards Working Group has put forth a tiered system of microscopy calibration and metadata standards for images obtained through fluorescence microscopy. The proposal is an extension of the OME data model and aims at increasing data fidelity, ease future analysis, and facilitate objective comparison of different datasets, experimental setups, and essays
results. Microscopy images must be accompanied by complete descriptions of experimental procedures, biological samples, microscope hardware specifications, image acquisition parameters, and metrics detailing instrument performance and calibration. Despite considerable effort (Goldberg et al., 2005; Linkert et al., 2010), however, universal data standards and reporting guidelines for the fair (Wilkinson et al., 2016) assessment and comparison of microscopy data have not been established. To understand this discrepancy and propose a way forward, we examine the benefits, pitfalls, and limitations of shared standards for fluorescence microscopy