Image Data Management support at the University of Arizona
As of January 2023, the NIH has required a Data Management and Sharing plan for all new grant submissions. Data from imaging devices, like microscopes, can be problematic for research labs to manage because of the many possible dimensions (xyztλ, etc.) of the data, the large file sizes (often many gigabytes per file), and the tendency of vendors to create proprietary file formats that are difficult to open except in specific software. As part of a UArizona strategic initiative to create a secure online environment (Soteria) for researchers to work with and analyze patient-related data, two additional resources for working with specific kinds of image data were also launched.
OMERO is open-source client-server software that leverages Bio-Formats to enable the server software to open and view over 150 different proprietary image file formats using a web browser interface. Images can come from microscopes, slide scanners, DLSRs, medical imaging devices (DICOM format), gel readers, high-content screening instruments, and other sources. OMERO can import associated metadata from proprietary files, and users can create their own schemas for tagging data to make it easier to find later.
The UArizona instance of OMERO is currently working on several projects involving patient-related data. The image data is de-identified, but the data is named with unique record numbers such that it can securely be related (leveraging Soteria) to additional information in REDCap (clinically related data) and OpenSpecimen (biorepository data). OMERO is also useful for research labs that don’t have patient-related data, but still want to centralize and standardize their management of image data. Doug Cromey (SWEHSC CIFC Director) is the contact for labs interested in learning more about OMERO (please email RII-OMERO@arizona.edu). For those curious about OMERO, Cromey has created a short (~25 min) presentation titled OMERO and Image Data Management that is available online (YouTube). In addition, recorded training sessions from an August 2023 workshop are available on a D2L website.
For those working primarily with medical imaging data in the DICOM format, an XNAT server has been set up at UArizona. XNAT is open-source software that facilitates common management, productivity, and quality assurance tasks for imaging and associated data.1 For more information on XNAT, please contact Dr. Chidi Ugonna (chidiugonna@arizona.edu).
It is important to note that both the OMERO and XNAT servers at the University of Arizona require that clinical or human subject-related data be de-identified.
1 About XNAT: https://www.xnat.org/about/