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Introduction: The International Society for Advancement of Cytometry (ISAC) has created a standard for the Minimum Information about a Flow Cytometry Experiment (MIFlowCyt 1.0). CytometryML will serve as a common metadata standard for flow and image cytometry (digital microscopy). Methods: The MIFlowCyt data-types were created, as is the rest of CytometryML, in the XML Schema Definition Language (XSD1.1). The datatypes are primarily based on the Flow Cytometry and the Digital Imaging and Communication (DICOM) standards. A small section of the code was formatted with standard HTML formatting elements (p, h1, h2, etc.). Results:1) The part of MIFlowCyt that describes the Experimental Overview including the specimen and substantial parts of several other major elements has been implemented as CytometryML XML schemas (www.cytometryml.org). 2) The feasibility of using MIFlowCyt to provide the combination of an overview, table of contents, and/or an index of a scientific paper or a report has been demonstrated. Previously, a sample electronic publication, EPUB, was created that could contain both MIFlowCyt metadata as well as the binary data. Conclusions: The use of CytometryML technology together with XHTML5 and CSS permits the metadata to be directly formatted and together with the binary data to be stored in an EPUB container. This will facilitate: formatting, data- mining, presentation, data verification, and inclusion in structured research, clinical, and regulatory documents, as well as demonstrate a publication’s adherence to the MIFlowCyt standard, promote interoperability and should also result in the textual and numeric data being published using web technology without any change in composition.

Introduction: The International Society for Advancement of Cytometry (ISAC) Data Standards Task Force (DSTF) has created a standard for the Minimum Information about a Flow Cytometry Experiment (MIFlowCyt 1.0). The CytometryML schemas, are based in part upon the Flow Cytometry Standard and Digital Imaging and Communication (DICOM) standards. CytometryML has and will be extended and adapted to include MIFlowCyt, as well as to serve as a common standard for flow and image cytometry (digital microscopy). Methods: The MIFlowCyt data-types were created, as is the rest of CytometryML, in the XML Schema Definition Language (XSD1.1). Individual major elements of the MIFlowCyt schema were translated into XML and filled with reasonable data. A small section of the code was formatted with HTML formatting elements. Results: The differences in the amount of detail to be recorded for 1) users of standard techniques including data analysts and 2) others, such as method and device creators, laboratory and other managers, engineers, and regulatory specialists required that separate data-types be created to describe the instrument configuration and components. A very substantial part of the MIFlowCyt element that describes the Experimental Overview part of the MIFlowCyt and substantial parts of several other major elements have been developed. Conclusions: The future use of structured XML tags and web technology should facilitate searching of experimental information, its presentation, and inclusion in structured research, clinical, and regulatory documents, as well as demonstrate in publications adherence to the MIFlowCyt standard. The use of CytometryML together with XML technology should also result in the textual and numeric data being published using web technology without any change in composition. Preliminary testing indicates that CytometryML XML pages can be directly formatted with the combination of HTML and CSS.

Background Flow Cytometry Standard (FCS) was initially created to standardize the software researchers use to analyze, transmit, and store data produced by flow cytometers and sorters. Because of the clinical utility of flow cytometry, it is necessary to have a standard consistent with the requirements of medical regulatory agencies. Methods We extended the existing mapping of FCS to the Digital Imaging and Communications in Medicine (DICOM) standard to include list-mode data produced by flow cytometry, laser scanning cytometry, and microscopic image cytometry. FCS list-mode was mapped to the DICOM Waveform Information Object. We created a collection of Extensible Markup Language (XML) schemas to express the DICOM analytical cytologic text-based data types except for large binary objects. We also developed a cytometry markup language, CytometryML, in an open environment subject to continuous peer review. Results The feasibility of expressing the data contained in FCS, including list-mode in DICOM, was demonstrated; and a preliminary mapping for list-mode data in the form of XML schemas and documents was completed. DICOM permitted the creation of indices that can be used to rapidly locate in a list-mode file the cells that are members of a subset. DICOM and its coding schemes for other medical standards can be represented by XML schemas, which can be combined with other relevant XML applications, such as Mathematical Markup Language (MathML). Conclusions The use of XML format based on DICOM for analytical cytology met most of the previously specified requirements and appears capable of meeting the others; therefore, the present FCS should be retired and replaced by an open, XML-based, standard CytometryML. Cytometry Part A 54A:56–65, 2003. © 2003 Wiley-Liss, Inc.

CytometryML is an XML schema based translation, extension and amalgamation of the DICOM and ISAC standards. CytometryML consists of 4 major XML schemas: Series, Instance, Instrument, and Specimen; it also includes Image and List-Mode schemas. Series metadata, which is specific for an entire collection of images and/or list-mode files produced by a single instrument and derived from a single specimen, is stored together with associated metadata files in a container (ZIP) file. Each Instance container file includes binary image and/or list-mode files together with associated metadata files that are specific for a single or closely related group of instrument runs from a single specimen. The Archival Cytometry Standard (ACS) proposed Table of Contents schema including its Resource Description Framework (RDF) capabilities has been extended and modified for use in the Instance schema.

The goal of this work is to develop a safe software construction means for an XML based data standard for a class of medical devices, cytometry instruments. Unfortunately, the amount of empirical evidence to archive this goal is minimal. Therefore, technologies associated with high reliability were employed together with reuse of existing designs. The basis for a major part of the design was the Digital Imaging and Communications in Medicine (DICOM) standard and the Flow Cytometry Standard (FCS). Since the DICOM Standard is a Class II device, the safety of software should be maximized. The XML Schema Definition Language (XSDL) has been used to develop schemas that maximize readability, modularity, strong typing, and reuse. An instance and an instrument XML schema were created for data obtained with a microscope by importing multiple schemas that each consisted of a class that described one object. This design was checked by validating the schemas and creating XML pages from them.

Introduction: The International Society for the Advancement of Cytometry (ISAC) Data Standards Task Force (DSTF) is developing a new Advanced Cytometry Specification (ACS). DICOM has developed and is extending a pathology extension. The work of both groups is complementary with some overlap. Interoperation would benefit both groups and permit each to benefit from the other’s expertise. Methods: The design and implementation of the CytometryML version of the ACS schemas have been based on each schema describing one object (modularity), iterative (spiral) development, inheritance, and reuse of data-types and their definitions from DICOM, Flow Cytometry Standard, and other standards. Results: These schemas have been validated with two tools and XML pages were generated from highest level schemas. Binary image data and its associated metadata are stored together in a zip file based container. A schema for a table of contents, which is one of the metadata files of this container, has recently been developed and reported upon. The binary image data is placed in one file in the container; and the metadata associated with an image in another. The schema for the image metadata file includes elements that are based on the DICOM design. This image schema includes descriptions of the acquisition context, image (including information on compression), specimen, slide, transmission medium, major optical parts, optical elements in one or more optical channels, detectors, and pixel format. The image schema describes both conventional camera systems and scanning or confocal systems.

Introduction: The highest priority for the Advanced Cytometry Standard (ACS) is the interpretation of list-mode cytometry measurements. Other priorities of lesser importance are the capacity to reproduce a cytometry measurement and the implementation of a digital microscopy image standard. The sequential nature of these requirements is being accommodated by a flexible, modular design. A major feature of this modular design is the creation of a design for an Advanced Cytometry Standard Container (ACSC) that includes a Table of Contents (ToC) XML file, one or more binary data containing files and files that contain the meta-data that describes the binary data. Methods: The design and partial implementation of the CytometryML schemas have been based on the techniques of modularity (each schema describing one object), iterative (spiral) development, inheritance, and reuse. Data-types including their definitions have been reused from DICOM, FCS, and other standards. Results: A prototype ToC schema together with prototypes of many of the schemas that describe the contents of the ACSC have been created together with their supporting schemas. These schemas have been validated with two tools and XML pages were generated from the main element(s) of the highest level schemas. These elements describe the table of contents of the zipped container file and a flow-cytometry instrument. The zipped container file (ACSC) describes and contains the meta and binary data.

The flow cytometry data file standard provides the specifications needed to completely describe flow cytometry data sets within the confines of the file containing the experimental data. In 1984, the first Flow Cytometry Standard format for data files was adopted as FCS 1.0. This standard was modified in 1990 as FCS 2.0 and again in 1997 as FCS 3.0. We report here on the next generation flow cytometry standard data file format. FCS 3.1 is a minor revision based on suggested improvements from the community. The unchanged goal of the standard is to provide a uniform file format that allows files created by one type of acquisition hardware and software to be analyzed by any other type.The FCS 3.1 standard retains the basic FCS file structure and most features of previous versions of the standard. Changes included in FCS 3.1 address potential ambiguities in the previous versions and provide a more robust standard. The major changes include simplified support for international characters and improved support for storing compensation. The major additions are support for preferred display scale, a standardized way of capturing the sample volume, information about originality of the data file, and support for plate and well identification in high throughput, plate based experiments. Please see the normative version of the FCS 3.1 specification in Supporting Information for this manuscript (or at http://www.isac-net.org/ in the Current standards section) for a complete list of changes.

Introduction: The International Society for Analytical Cytology, ISAC, is developing a new combined flow and image Analytical Cytometry Standard (ACS). This standard needs to serve both the research and clinical communities. The clinical medicine and clinical research communities have a need to exchange information with hospital and other clinical information systems. Methods: 1) Prototype the standard by creating CytometryML and a RAW format for binary data. 2) Join the ISAC Data Standards Task Force. 3) Create essential project documentation. 4) Cooperate with other groups by assisting in the preparation of the DICOM Supplement 122: Specimen Module and Pathology Service-Object Pair Classes. Results: CytometryML has been created and serves as a prototype and source of experience for the following: the Analytical Cytometry Standard (ACS) 1.0, the ACS container, Minimum Information about a Flow Cytometry Experiment (MIFlowCyt), and Requirements for a Data File Standard Format to Describe Flow Cytometry and Related Analytical Cytology Data. These requirements provide a means to judge the appropriateness of design elements and to develop tests for the final ACS. The requirements include providing the information required for understanding and reproducing a cytometry experiment or clinical measurement, and for a single standard for both flow and digital microscopic cytometry. Schemas proposed by other members of the ISAC Data Standards Task Force (e.g, Gating-ML) have been independently validated and have been integrated with CytometryML. The use of netCDF as an element of the ACS container has been proposed by others and a suggested method of its use is proposed.

Because of the differences in the requirements, needs, and past histories including existing standards of the creating organizations, a single encompassing cytology-pathology standard will not, in the near future, replace the multiple existing or under development standards. Except for DICOM and FCS, these standardization efforts are all based on XML. CytometryML is a collection of XML schemas, which are based on the Digital Imaging and Communications in Medicine (DICOM) and Flow Cytometry Standard (FCS) datatypes. The CytometryML schemas contain attributes that link them to the DICOM standard and FCS. Interoperability with DICOM has been facilitated by, wherever reasonable, limiting the difference between CytometryML and the previous standards to syntax. In order to permit the Resource Description Framework, RDF, to reference the CytometryML datatypes, id attributes have been added to many CytometryML elements. The Laboratory Digital Imaging Project (LDIP) Data Exchange Specification and the Flowcyt standards development effort employ RDF syntax. Documentation from DICOM has been reused in CytometryML. The unity of analytical cytology was demonstrated by deriving a microscope type and a flow cytometer type from a generic cytometry instrument type. The feasibility of incorporating the Flowcyt gating schemas into CytometryML has been demonstrated. CytometryML is being extended to include many of the new DICOM Working Group 26 datatypes, which describe patients, specimens, and analytes. In situations where multiple standards are being created, interoperability can be facilitated by employing datatypes based on a common set of semantics and building in links to standards that employ different syntax.

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.

Cytometry Markup Language, CytometryML, is a proposed new analytical cytology data standard. CytometryML is a set of XML schemas for encoding both flow cytometry and digital microscopy text based data types. CytometryML schemas reference both DICOM (Digital Imaging and Communications in Medicine) codes and FCS keywords. These schemas provide representations for the keywords in FCS 3.0 and will soon include DICOM microscopic image data. Flow Cytometry Standard (FCS) list-mode has been mapped to the DICOM Waveform Information Object. A preliminary version of a list mode binary data type, which does not presently exist in DICOM, has been designed. This binary type is required to enhance the storage and transmission of flow cytometry and digital microscopy data. Index files based on Waveform indices will be used to rapidly locate the cells present in individual subsets. DICOM has the advantage of employing standard file types, TIF and JPEG, for Digital Microscopy. Using an XML schema based representation means that standard commercial software packages such as Excel and MathCad can be used to analyze, display, and store analytical cytometry data. Furthermore, by providing one standard for both DICOM data and analytical cytology data, it eliminates the need to create and maintain special purpose interfaces for analytical cytology data thereby integrating the data into the larger DICOM and other clinical communities. A draft version of CytometryML is available at www.newportinstruments.com.

Flow cytometry data can be directly mapped to the Digital Imaging and Communications in Medicine, DICOM standard. A preliminary mapping of list-mode data to the DICOM Waveform information Object will be presented. This mapping encompasses both flow and image list-mode data. Since list- mode data is also produced by digital slide microscopy, which has already been standardized under DICOM, both branches of Analytical Cytology can be united under the DICOM standard. This will result in the functionality of the present International Society for Analytical Cytology Flow Cytometry Standard, FCS, being significantly extended and the elimination of the previously reported FCS design deficiencies. Thus, the present Flow Cytometry Standard can and should be replaced by a Digital Imaging and Communications in Medicine, DICOM, standard. Expression of Analytical Cytology data in any other format, such as XML, can be made interoperable with DICOM by employing the DICOM data types. A fragment of an XML Schema has been created, which demonstrates the feasibility of expressing DICOM data types in XML syntax. The extension of DICOM to include Flow Cytometry will have the benefits of 1) retiring the present FCS, 2) providing a standard that is ubiquitous, internationally accepted, and backed by the medical profession, and 3) inter-operating with the existing medical informatics infrastructure.

1. ABSTRACT The combination of Ada's new class-wide programming with tagged types, generics, and representation clauses for both enumerated and record types greatly facilitates low level programing. A generic board register class was extended to represent the specific hardware and provide high level abstractions for reading and changing the states of the hardware registers. Subprograms included in this generic board register class include functions and procedures which address these registers by name and employ high-level syntax for bit manipulation. The use of these objects derived from the register class permits the development of easily understood, maintainable software for computer boards which control and acquire data from devices including scientific and medical instruments. A software library providing these and other relevant functionalities and an application with a commercial 100 megahertz scaler board for a PC will be described.

Two existing Ada tools AdaSAGE and AYACC were combined to produce a system that parses International Society for Analytical Cytology, ISAC, Flow Cytometry Standard 2.0 files and stores the data in AdaSAGE tables. There are significant differences in the way manufacturers interpret and conform to Flow Cytometry Standard 2.0. AdaSAGE is employed to analyze and plot the data from multiple experiments. This data is used to assess the stability of flow cytometers. The initial release will be for DOS. The utilization of AdaSAGE, which is a flexible database tool, will facilitate subsequent development of other products. The software engineer, whose previous professional experience was with C and C++, had very few problems with Ada syntax. The interface to the compiler and other tools was immature compared to those available for C++. The DOS text based user interface environment provided by AdaSAGE limited the functionality of the user interface. However, the present DOS 386 program can be directly ported to the newly released version of AdaSAGE for Microsoft Windows 95. Ada’s strong type checking and package structure have significantly facilitated the development of the product.

XML has become a major Internet technology. The programing language that has the best fit with XML is Ada. XML and Ada have similar typing systems, visibility and scoping rules. A mutually beneficial symbiosis requires the creation of applications in Ada that use and support XML, as well as, the use of XML to create Ada environments including XML based tools. Ada and XML. A small example of this relationship will be illustrated with results from the development of an XML based biomedical standard, CytometyML.