This module invites you to learn the basics behind collecting and reporting microscopy metadata including guidelines and tools.
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.
Presenter: Caterina Strambio De Castillia, UMass Chan Medical School, USA
Open access Nature Methods article describing community-driven metadata standrds for light microsopy.
This module invites you to learn how to use Micro-Meta App, a free open-source software for collecting microscopy metadata.
Micro-Meta App is an intuitive, highly interoperable, open-source software tool that is designed to facilitate the extraction and collection of relevant microscopy metadata as specified by the recent 4DN-BINA-OME tiered-system of Microscopy Metadata specifications. In addition to substantially lowering the burden of quality assurance, the visual nature of Micro-Meta App makes it particularly suited for training purposes.
Download and learn more about Micro-Meta App at the link above.
A step-by-step written tutorial explaining how to get started with the Micro-Meta App.
Presenter: Caterina Strambio De Castillia, UMass Chan Medical School, USA
Presenter: Caterina Strambio De Castillia, UMass Chan Medical School, USA
Presenter: Caterina Strambio De Castillia, UMass Chan Medical School, USA
Presenter: Caterina Strambio De Castillia, UMass Chan Medical School, USA
Presenter: Caterina Strambio De Castillia, UMass Chan Medical School, USA
Presenter: Caterina Strambio De Castillia, UMass Chan Medical School, USA
Presenter: Caterina Strambio De Castillia, UMass Chan Medical School, USA
Download example metadata files at the link above to test Micro-Meta App.
Open access Nature Methods article describing Micro-Meta App.
This module invites you to learn how to use MethodsJ2, a Python script for Fiji for generating methods text for the use in publications and reports.
MethodsJ2 is a Python script for Fiji and it helps researchers to write materials and methods text for microscopy experiments by sourcing experiment information from metadata, as well as information from a microscope hardware configuration file generated in Micro-Meta App. A draft experiment methods section text is generated by MethodsJ2 which can then be revised by a user and used in written manuscripts and reports.
Presenter: Joel Ryan, McGill University, Canada
Presenter: Joel Ryan, McGill University, Canada
Presenter: Joel Ryan, McGill University, Canada
Presenter: Joel Ryan, McGill University, Canada
Download and learn more about MethodsJ2 Python script at the link above.
Open access Nature Methods article describing MethodsJ2.
Recommended Metadata for Biological Images (REMBI) is a draft of metadata guidelines within light and electron microscopy proposed by EMBL’s European Bioinformatics Institute (EMBL-EBI) and colleagues at over 30 other institutions in different bioimaging communities, including light, electron and X-ray microscopy communities.
REMBI aims to enable wider sharing and reuse of bioimaging data and is planned to be adopted by the BioImage Archive, EMPIAR, Cell-IDR and Tissue-IDR databases.
Presenter: Laura Cooper, University of Warwick, United Kingdom
Presenter: Laura Cooper, University of Warwick, United Kingdom
Presenter: Laura Cooper, University of Warwick, United Kingdom
Presenter: Laura Cooper, University of Warwick, United Kingdom
Presenter: Laura Cooper, University of Warwick, United Kingdom
Presenter: Laura Cooper, University of Warwick, United Kingdom
Presenter: Laura Cooper, University of Warwick, United Kingdom
Presenter: Laura Cooper, University of Warwick, United Kingdom
Presenter: Laura Cooper, University of Warwick, United Kingdom
Presenter: Laura Cooper, University of Warwick, United Kingdom
The current version of REMBI can be viewed in the Google Sheets accessible at the link above.
The information on modules, attributes, data entry methods, relevant existing standards and ontologies can be found there.
FAIRsharing registry contains REMBI entry accessible at the link above.
Open access Nature Methods article describing REMBI and the proposed metadata guidelines within light and electron microscopy to enable reuse of bioimaging data.
This project has been made possible in part by a grant from the Chan Zuckerberg Initiative DAF, an advised fund of Silicon Valley Community Foundation.
