Open image informatics software for biological microscopy

Biological microscopy has always required an imaging capability: traditionally, an image of a sample was drawn on paper, or with the advent of light-sensitive film, recorded on media that conveniently allowed reproduction. However, the application of digital detectors to microscopy has converted the biological microscope into a quantitative assay device. The clinical and research applications for digital imaging microscopy are enormous, but these applications generate large amounts of data/a single time-lapse image can easily be 500 Mbytes. Four years ago, we began developing a data management tool for digital biological microscopy. Our project, the Open Microscopy Environment (OME; http://openmicroscopy.org) is now the leading provider of open source image management software for biological microscopy. This proposal seeks funds to support the integration of image data storage technology created by OME with genome sequencing data generated over the last ten years. The genome sequences of humans and many of the organisms used in modern biomedical research are now known and available on the Web (e.g., http://www.fllybase.org). However, there is an increasingly rich set of accessory images showing effects of genetic mutations, gene expression, etc. that should be served by these sites, but no standard data format is available to allow delivery or sharing of this information with or between researchers. We will therefore incorporate the experimental data models built by other projects into the existing OME Data Model that describes the results of an imaging experiment, and develop tools to help scientists record experimental data about an imaging experiment (e.g., kinds of cells, gene mutations) in a single, coherent, shareable format. Finally, as the OME project grows, we have real need for resources for generating user-targeted documentation, FAQ's, etc., as well as managing user and developer questions. Currently, our developers are providing these services, but we have no resources for managing or logging contacts, and ensuring coherent support is provided. This support will go a long way to ensuring the usefulness and dissemination of the OME tools.

Biological imaging is now used as an assay technique, most recently in time-lapse multichannel fluorescence imaging of cellular dynamics and in high-content genomic or small molecule screens. Maintaining critical contextual descriptions (e.g., cell lines, mutants, microscope configuration), the relationships between images, annotations and quantitative analyses while preventing data loss during file format migration or data exchange with collaborators is a major challenge for any cell biologist. Our project, the Open Microscopy Environment (OME; http://openmicroscopy.org) solves this problem with a Data Model that simultaneously defines the relationships between complex data types and provides a mechanism for changes to the Data Model to support changing experimental requirements. However, the OME Data Model is focused on capturing image metadata. Now that mature experimental ontologies are available from MGED, GO, and OBO, we will incorporate the appropriate parts of these models into the OME Data Model to generate a fully functional data model for biological microscopy. In addition, we will evaluate, and if necessary update existing freely available tools for data capture (e.g., Protege) so that not only microscope image data, but also all experimental metadata, are easily entered by the user into the data management tools provide by OME. Finally, we will initiate a user and developer support system for OME, to ensure that feedback and requests are properly managed and supported.