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

Johnny Hay, Eilidh Troup, Ivan Clark, Julian Pietsch, Tomasz Zielinski, Andrew J Millar

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

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 present PyOmeroUpload, 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
Original languageEnglish
JournalWellcome Open Research
DOIs
Publication statusPublished - 18 May 2020

Keywords / Materials (for Non-textual outputs)

  • data sharing
  • research data management
  • microscopy
  • OMERO
  • metadata
  • docker

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