CytometryML, Binary Data Standards

摘要

CytometryML is a proposed new Analytical Cytology (Cytomics) data standard, which is based on a common set of XML schemas for encoding flow cytometry and digital microscopy text based data types (metadata). CytometryML schemas reference both DICOM (Digital Imaging and Communications in Medicine) codes and FCS keywords. Flow Cytometry Standard (FCS) list-mode has been mapped to the DICOM Waveform Information Object. The separation of the large binary data objects (list mode and image data) from the XML description of the metadata permits the metadata to be directly displayed, analyzed, and reported with standard commercial software packages; the direct use of XML languages; and direct interfacing with clinical information systems. The separation of the binary data into its own files simplifies parsing because all extraneous header data has been eliminated. The storage of images as two-dimensional arrays without any extraneous data, such as in the Adobe® Photoshop® RAW format, "facilitates the development by scientists of their own analysis and visualization software. Adobe Photoshop provided the display infrastructure and the translation facility to interconvert between the image data from commercial formats and RAW format. Similarly, the storage and parsing of list mode binary data type with a group of parameters that are specified at compilation time is straight forward. However when the user is permitted at run-time to select a subset of the parameters and/or specify results of mathematical manipulations, the development of special software was required. The use of CytometryML will permit investigators to be able to create their own interoperable data analysis software and to employ commercially available software to disseminate their data.