RESUMEN
Open access to data underpinning published results is a key pillar of scientific reproducibility. Making data available at scale also provides opportunities for data reuse, encouraging the development of new analysis approaches. In this poster article, accompanying a recorded talk, we will explain the benefits of publicly archiving your image data alongside your published manuscripts, as well as highlight what resources are available to do this. This will include the BioImage Archive, EMBL-EBI's new resource for biological image data, https://www.ebi.ac.uk/bioimage-archive/. We will look at how image data submission works, how to prepare in advance for archiving your data and upcoming developments.
RESUMEN
Biological imaging is one of the primary tools by which we understand living systems across scales from atoms to organisms. Rapid advances in imaging technology have increased both the spatial and temporal resolutions at which we examine those systems, as well as enabling visualisation of larger tissue volumes. These advances have huge potential but also generate ever increasing amounts of imaging data that must be stored and analysed. Public image repositories provide a critical scientific service through open data provision, supporting reproducibility of scientific results, access to reference imaging datasets and reuse of data for new scientific discovery and acceleration of image analysis methods development. The scale and scope of imaging data provides both challenges and opportunities for open sharing of image data. In this article, we provide a perspective influenced by decades of provision of open data resources for biological information, suggesting areas to focus on and a path towards global interoperability.
Asunto(s)
Procesamiento de Imagen Asistido por Computador , Reproducibilidad de los ResultadosRESUMEN
A growing community is constructing a next-generation file format (NGFF) for bioimaging to overcome problems of scalability and heterogeneity. Organized by the Open Microscopy Environment (OME), individuals and institutes across diverse modalities facing these problems have designed a format specification process (OME-NGFF) to address these needs. This paper brings together a wide range of those community members to describe the cloud-optimized format itself -- OME-Zarr -- along with tools and data resources available today to increase FAIR access and remove barriers in the scientific process. The current momentum offers an opportunity to unify a key component of the bioimaging domain -- the file format that underlies so many personal, institutional, and global data management and analysis tasks.