Abstract:
An American National Standard
Developed by the
National Information Standards Organization
Approved: July 9, 2012
by the
American National Standards Institutue
About NISO Standards
NISO standards are developed by the Working Groups of the National Information Standards Organization (NISO) with oversight from a Topic Committee. The development process is a strenuous one that includes a rigorous peer review of proposed standards open to each NISO Voting Member and any other interested party. Final approval of the standard involves verification by the American National Standards Institute that its requirements for due process, consensus, and other approval criteria have been met by NISO. Once verified and approved, NISO Standards also become American National Standards.
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Copyright © 2012 by the National Information Standards Organization
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ISBN: 978-1-937522-06-3 (HTML)
ISBN: 978-1-937522-07-0 (PDF)
Table of Contents
List of Examples
xmlns
attribute
container.xml
file mark up
(This foreword is not part of the Authoring and Interchange Framework for Adaptive XML Publishing Specification, ANSI/NISO Z39.98-2012. It is included for information only.)
The Z39.98 Authoring and Interchange Framework for Adaptive XML Publishing Specification (Z39.98-AI) defines a framework in which to develop XML markup languages to represent different kinds of information resources (books, periodicals, etc.), with the intent of producing documents suitable for transformation into different universally accessible formats. It uses a modular, extensible architecture to permit the creation of any number of document models, each custom-tailored for a particular kind of information resource.
This approach to text production differs significantly from the one taken in ANSI/NISO Z39.86-2005 (the DTBook grammar), which attempted to provide a single markup model in which all formats could be present (i.e., a single universal rendering format). Although the Z39.86 approach has potential merits for reader consumption, it could not provide the richness needed by producers in many cases to render high-quality individual outputs. Producing print braille compliant to regional codes, as one example, was complicated by markup that was often more generally useful for refreshable braille display. Accessible production by needs requires the ability to repurpose content in a variety of forms for readers of different abilities, and as efficiently as possible, but this need that DTBook also hoped to address was not being fully realized.
The Z39.86 text model was further complicated in that it could not be easily redefined for specific use cases. All content had to be structured exactly the same way, regardless of the form it took in its source. By focusing on accessible output requirements, it was also not widely useful as a production format for mainstream publishing requirements, limiting the ability to obtain content from source producers.
This standard escapes the trap of defining markup models and instead focuses on a general, extensible and highly-adaptable framework in which content models can be defined. It prescribes the rules and requirements for predictable and rapid development of new content models without defining specifically defining the grammars. The development of single source master documents that can be easily exchanged between organizations is the ultimate goal, but without imposing limits on the markup expressivity needs of any individual producer.
The richness of markup that can be produced using this model also places this standard back in the mainstream. Its focus on fully representing the structure and meaning of the documents being described makes it a candidate for use in any environment in which a parallel publishing model is currently used or envisioned. The outputs that can be generated from documents that conform to Z39.98-AI profiles are not limited to accessible formats.
Z39.98-AI was originally intended to be a revision to and replacement for ANSI/NISO Z39.86, Specifications for the Digital Talking Book. After consideration of feedback from the draft for trial use of the proposed revision, the Working Group recommended that the revision be given a new standard designation number and that the existing Z39.86 standard be reaffirmed. Trial users had indicated that the changes were so significant as to warrant this being a new standard. Additionally, content creators, software developers, and e-reader device manufacturers wanted to continue using the existing standard for the near future while they developed transition plans to the new standard. The NISO Content and Collection Management Topic Committee approved the Working Group's recommendation and this standard was assigned the new designation of Z39.98. Subsequently, ANSI/NISO Z39.86 was reaffirmed for another five years.
Wherever used in this standard, all terms that are trademarks or service marks are and remain the property of their respective owners.
At the time this standard was approved, the following were members of the NISO Voting Pool:
American Library Association (ALA) Nancy Kraft
American Psychological Association Linda Beebe Janice Fleming
American Society for Indexing Judith Gibbs
American Society for Information Science & Technology (ASIS&T) Mark Needleman
Association of Research Libraries (ARL) Julia Blixrud Charles Lowry
College Center for Library Automation (CCLA) David Brightbill Lucy Harrison
DAISY Consortium George Kerscher Markus Gylling
Inera Inc. Bruce Rosenblum
ITHAKA/JSTOR/Portico Bruce Heterick Amy Kirchhoff
Library of Congress Sally McCallum John Zagas
Lyrasis Robin Dale Tim Daniels Peter Murray
Music Library Association Mark McKnight David Sommerfield
National Archives and Records Administration (NARA) Laura McCarthy Marilyn Redman
National Library of Medicine (NLM) Barbara Rapp Jacque-Lynne Schulman
National Security Agency Kate Dolan Kathleen Rattell
Polaris Library Systems Eric Graham Paul Huf
Recording Industry Association of America (RIAA) David Hughes Paul Jessop
At the time this standard was approved, the following individuals served on the NISO Content and Collection Management Topic Committee that had oversight for the development of this standard:
Julia Blixrud Association of Research Libraries (ARL)
Eva Bolkovac Yale University Library
Lettie Conrad SAGE Publications
Diane Hillmann Syracuse University
Marjorie Hlava Access Innovations, Inc.
Rebecca Kennison Columbia University
Betty Landesman NIH Library
Rice Majors University of Colorado at Boulder
Dorothea Salo University of Wisconsin, Madison
Ken Wells Innovative Interfaces, Inc.
The following are the members of the Z39.98-AI Working Group responsible for the development of this standard:
Markus Gylling, Lead DAISY Consortium
Josh Altherr gh, LLC
Ole Holst Andersen DBB
Marisa DeMeglio DAISY Consortium
Christian Egli Swiss Library for the Blind, Visually Impaired and Print Disabled
Matt Garrish CNIB
Boris Goldowsky CAST, Inc.
Leona Holloway Vision Australia
Kenny Johar Vision Australia
Dennis Leas gh, LLC
Sam Ogami California State University
Stephen Phippen RNIB
James Pritchett Learning Ally
Kathryn Randall Vision Australia
Per Sennels Huseby kompetansesenter
The metadata portion of this standard was created by a working group with the following members:
Matt Garrish, Lead CNIB
Bob Axtell Library of Congress
Wendy Taylor RNIB
Christian Wallin DBB
Marcus Westlind TPB
Richard Wilson CNIB
This specification details the nature of Z39.98 Authoring and Interchange Format (Z39.98-AI) profiles and how they are created. It is intended primarily for agencies interested in creating conformant profiles for new documents types and for processing agent developers.
This specification is not a guide to marking up Z39.98-AI documents and should not be referenced as such. Informative resources that describe Z39.98-AI document production are available independently of this specification.
Although this specification contains introductory sections where appropriate and deals with general document concepts in places, it is expected that all persons reading this specification will have a strong background in XML and its related technologies — in particular schema languages and their composition — in order to properly implement new profiles.
The Z39.98-AI Framework has been built with the following primary design goals in mind:
Adaptability. The Framework is designed to be flexible and customizable across a wide variety of production environments. Producers ar