Open tools for storage and management of quantitative image data

Joshua Moore, Chris Allan, Jean-Marie Burel, Brian Loranger, Donald MacDonald, Jonathan Monk, Jason R. Swedlow

    Research output: Chapter in Book/Report/Conference proceedingOther chapter contribution

    24 Citations (Scopus)

    Abstract

    The explosion in quantitative imaging has driven the need to develop tools for storing, managing, analyzing, and viewing large sets of data. In this chapter, we discuss tools we have built for storing large data sets for the lifetime of a typical research project. As part of the Open Microscopy Environment (OME) Consortium, we have built a series of open-source tools that support the manipulation and visualization of large sets of complex image data. Images from a number of proprietary file formats can be imported and then accessed from a single server running in a laboratory or imaging facility. We discuss the capabilities of the OME Server, a Perl-based data management system that is designed for large-scale analysis of image data using a web browser-based user interface. In addition, we have recently released a lighter weight Java-based OME Remote Objects Server that supports remote applications for managing and viewing image data. Together these systems provide a suite of tools for large-scale quantitative imaging that is now commonly used throughout cell and developmental biology.

    Original languageEnglish
    Title of host publication Fluorescent Proteins
    Place of PublicationSan Diego
    PublisherAcademic Press
    Pages555-+
    Number of pages20
    Volume85
    Edition2nd
    DOIs
    Publication statusPublished - 2008

    Publication series

    NameMethods in Cell Biology
    PublisherElsevier
    Volume85

    Keywords

    • OPEN MICROSCOPY ENVIRONMENT
    • INFORMATICS

    Cite this

    Moore, J., Allan, C., Burel, J-M., Loranger, B., MacDonald, D., Monk, J., & Swedlow, J. R. (2008). Open tools for storage and management of quantitative image data. In Fluorescent Proteins (2nd ed., Vol. 85, pp. 555-+). (Methods in Cell Biology; Vol. 85). San Diego: Academic Press. https://doi.org/10.1016/S0091-679X(08)85024-8
    Moore, Joshua ; Allan, Chris ; Burel, Jean-Marie ; Loranger, Brian ; MacDonald, Donald ; Monk, Jonathan ; Swedlow, Jason R. / Open tools for storage and management of quantitative image data. Fluorescent Proteins. Vol. 85 2nd. ed. San Diego : Academic Press, 2008. pp. 555-+ (Methods in Cell Biology).
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    Moore, J, Allan, C, Burel, J-M, Loranger, B, MacDonald, D, Monk, J & Swedlow, JR 2008, Open tools for storage and management of quantitative image data. in Fluorescent Proteins. 2nd edn, vol. 85, Methods in Cell Biology, vol. 85, Academic Press, San Diego, pp. 555-+. https://doi.org/10.1016/S0091-679X(08)85024-8

    Open tools for storage and management of quantitative image data. / Moore, Joshua; Allan, Chris; Burel, Jean-Marie; Loranger, Brian; MacDonald, Donald; Monk, Jonathan; Swedlow, Jason R.

    Fluorescent Proteins. Vol. 85 2nd. ed. San Diego : Academic Press, 2008. p. 555-+ (Methods in Cell Biology; Vol. 85).

    Research output: Chapter in Book/Report/Conference proceedingOther chapter contribution

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    AU - Monk, Jonathan

    AU - Swedlow, Jason R.

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    AB - The explosion in quantitative imaging has driven the need to develop tools for storing, managing, analyzing, and viewing large sets of data. In this chapter, we discuss tools we have built for storing large data sets for the lifetime of a typical research project. As part of the Open Microscopy Environment (OME) Consortium, we have built a series of open-source tools that support the manipulation and visualization of large sets of complex image data. Images from a number of proprietary file formats can be imported and then accessed from a single server running in a laboratory or imaging facility. We discuss the capabilities of the OME Server, a Perl-based data management system that is designed for large-scale analysis of image data using a web browser-based user interface. In addition, we have recently released a lighter weight Java-based OME Remote Objects Server that supports remote applications for managing and viewing image data. Together these systems provide a suite of tools for large-scale quantitative imaging that is now commonly used throughout cell and developmental biology.

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    Moore J, Allan C, Burel J-M, Loranger B, MacDonald D, Monk J et al. Open tools for storage and management of quantitative image data. In Fluorescent Proteins. 2nd ed. Vol. 85. San Diego: Academic Press. 2008. p. 555-+. (Methods in Cell Biology). https://doi.org/10.1016/S0091-679X(08)85024-8