Scalable strategies for interoperable bioimaging data

Abstract number
64
Presentation Form
Poster
DOI
10.22443/rms.elmi2021.64
Corresponding Email
[email protected]
Session
Poster Session 2
Authors
Josh Moore (1)
Affiliations
1. Open Microscopy Environment (OME)
Keywords

bioimaging, data formats, linked open data, FAIR, standards

Abstract text

Despite significant advances in biological imaging and analysis, major informatics challenges remain unsolved: file formats are proprietary, storage and analysis facilities are lacking, as are standards for sharing image data and results. 

The Open Microscopy Environment (OME) is an open-source software project that develops tools to enable access, analysis, visualization, sharing and publication of biological image data. OME supports more than 150 image data formats across many imaging modalities including fluorescence microscopy, high-content screening, whole-slide imaging and biomedical imaging.

OME releases specifications and software for managing image datasets and integrating them with other scientific data. OME’s Bio-Formats is a file translator that enables scientists to open and work with imaging data in the software application of their choice. OMERO is an image database application that provides data management and sharing capabilities to imaging scientists. Bio-Formats and OMERO are used in 1000’s of labs worldwide to enable discovery with imaging.

Additionally, we have used Bio-Formats and OMERO to build a system for publishing imaging data associated with peer-reviewed publications. The Image Data Resource (IDR) has published >80 studies and >260TB of imaging data annotated with >19,000 genes and 31,000 small molecules inhibitors and drugs. IDR includes a cloud-based analysis portal to catalyse the re-use and re-analysis of published imaging data.

Despite these efforts, there are still inherent limits in existing research infrastructure available for tackling the next scale of bioimaging: the cloud. As a result, OME in collaboration with collaborators and the community have begun defining a next-generation file format (OME-NGFF) to address these next challenges.

This poster explores  lessons learned over nearly two decades of supporting bioimaging scientists and their data formats, discusses our existing open file formats as well as those under development, and proposes strategies for the exchange of imaging data publishing and re-analyzing images.

References

Josh Moore, Chris Allan, Sebastien Besson, Jean-Marie Burel, Erin Diel, David Gault, Kevin Kozlowski, Dominik Lindner, Melissa Linkert, Trevor Manz, Will Moore, Constantin Pape, Christian Tischer, Jason R. Swedlow (2021) OME-NGFF: scalable format strategies for interoperable bioimaging data. bioRxiv 2021.03.31.437929; doi: https://doi.org/10.1101/2021.03.31.437929

Eleanor Williams, Josh Moore, Simon W. Li, Gabriella Rustici, Aleksandra Tarkowska, Anatole Chessel, Simone Leo, Bálint Antal, Richard K. Ferguson, Ugis Sarkans, Alvis Brazma, Rafael E. Carazo Salas, Jason R. Swedlow (2017) The Image Data Resource: A Bioimage Data Integration and Publication Platform. Nature Methods 14(8), 775-781. Published 19 June 2017 doi: https://doi.org/10.1038/nmeth.4326

Chris Allan, Jean-Marie Burel, Josh Moore, Colin Blackburn, Melissa Linkert, Scott Loynton, Donald MacDonald, William J Moore, Carlos Neves, Andrew Patterson, Michael Porter, Aleksandra Tarkowska, Brian Loranger, Jerome Avondo, Ingvar Lagerstedt, Luca Lianas, Simone Leo, Katherine Hands, Ron T Hay, Ardan Patwardhan, Christoph Best, Gerard J Kleywegt, Gianluigi Zanetti & Jason R Swedlow (2012) OMERO: flexible, model-driven data management for experimental biology. Nature Methods 9, 245–253. Published: 28 February 2012 doi: https://doi.org/10.1038/nmeth.1896

Melissa Linkert, Curtis T. Rueden, Chris Allan, Jean-Marie Burel, Will Moore, Andrew Patterson, Brian Loranger, Josh Moore, Carlos Neves, Donald MacDonald, Aleksandra Tarkowska, Caitlin Sticco, Emma Hill, Mike Rossner, Kevin W. Eliceiri, and Jason R. Swedlow (2010) Metadata matters: access to image data in the real world. The Journal of Cell Biology 189(5), 777-782. doi: https://doi.org/10.1083/jcb.201004104