arXiv subjects

Claire M. Brown

Publications and source records attributed to Claire M. Brown.

3 recordsLinked to original sources

arXiv2025

Harmonizing the Generation and Pre-publication Stewardship of FAIR Image Data

Alongside molecular insights into genes and proteins, biological imaging holds great promise for deepening scientific understanding of complex cellular systems and advancing predictive, personalized therapies for human health. To realize this potential, quality-assured image data must be shared globally across laboratories to enable comparison, pooling, and reanalysis-unlocking value far beyond the original purpose of data collection. Two broad sets of requirements are essential to enable image data sharing in the life sciences. The companion article Enabling Global Image Data Sharing in the Life Sciences outlines the need to develop cyberinfrastructure for sharing bioimage data. In this manuscript, we detail a broad set of requirements, which involves collecting, managing, presenting, and propagating contextual information essential to assess the quality, understand the content, interpret the scientific implications, and reuse bioimage data in the context of the experimental details. We start by providing an overview of the main lessons learned to date through international community activities, which have recently made considerable progress toward generating community standard practices for imaging Quality Control (QC) and metadata. We then provide a clear set of recommendations for amplifying this work. The driving goal is to address remaining challenges and democratize access to everyday practices and tools for a spectrum of biomedical researchers, regardless of their expertise, access to resources, and geographical location.

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arXiv2021

A perspective on Microscopy Metadata: data provenance and quality control

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].

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arXiv2020

A Global View of Standards for Open Image Data Formats and Repositories

Biological and biomedical imaging datasets record the constitution, architecture and dynamics of living organisms across several orders of magnitude of space and time. Imaging technologies are now used throughout the life and biomedical sciences to achieve discovery and understanding of biological mechanisms in the basic sciences as well as assessment, diagnosis and therapeutic intervention in clinical trials and animal and human medicine. The universal application and use of imaging raises an important question and opportunity: what is the value and ultimate destination of biological and medical imaging data? In the last few years, several informatics and data science technologies have matured sufficiently so that routine publication of these datasets is now possible. Participants in Global BioImaging from 15 countries and all populated continents have agreed on the need for recommendations and guidelines for the establishment of image data repositories and the formats they use for delivering data to the global scientific community. This white paper presents a shared, global view of criteria for these common, globally applicable guidelines and provisional proposals for open tools and resources that are available now and can provide a foundation for future development.

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