PyOmeroUpload: A Python toolkit for uploading images and metadata to OMERO

Wellcome Open Research

article

Johnny Hay¹  Eilidh Troup¹  Ivan Clark²  Julian Pietsch²  Tomasz Zieliński²  Andrew Millar² 

[1] EPCC, University of Edinburgh;SynthSys and School of Biological Sciences, University of Edinburgh

关键词: Data sharing;    research data management;    microscopy;    OMERO;    metadata;    Docker;   

DOI  :  10.12688/wellcomeopenres.15853.2

学科分类：内科医学

来源: Wellcome

【 摘 要 】

Tools and software that automate repetitive tasks, such as metadata extraction and deposition to data repositories, are essential for researchers to share Open Data, routinely. For research that generates microscopy image data, OMERO is an ideal platform for storage, annotation and publication according to open research principles. We presentPyOmeroUpload, a Python toolkit for automatically extracting metadata from experiment logs and text files, processing images and uploading these payloads to OMERO servers to create fully annotated, multidimensional datasets. The toolkit comes packaged in portable, platform-independent Docker images that enable users to deploy and run the utilities easily, regardless of Operating System constraints. A selection of use cases is provided, illustrating the primary capabilities and flexibility offered with the toolkit, along with a discussion of limitations and potential future extensions.PyOmeroUpload is available from:https://github.com/SynthSys/pyOmeroUpload.

【 授权许可】

CC BY