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Introduction to Authoring Tag Set

The intent of JATS is to provide a common format in which publishers and archives can exchange journal content. The Suite provides a set of XML schema modules that define elements and attributes for describing the textual and graphical content of journal articles as well as some non-article material such as letters, editorials, and book and product reviews.
Rationale
The Article Authoring Tag Set defines elements and attributes that describe the content and metadata of journal articles, including research articles; subject-review articles; non-research articles; letters; editorials; book, software, and product reviews; peer reviews, and author responses included with an article. The Tag Set allows for descriptions of the full article content and article header metadata.
The intent of the Authoring Tag Set is to create a standardized format for users to create new journal articles using model-driven tools (tools that read, interpret, and apply schemas in real time) and submit the articles to journals for publication consideration.
Because the Set is optimized for use with tools, Authoring is the most prescriptive Set in the overall Tag Suite. It includes many elements whose content must occur in a specified order and limits the options for formatting. For example, the Set does not allow explicit numbering on list items or citations. These are items that are determined by a journal’s editorial style and are not appropriate for inclusion in the Authoring Tag Set.
This Tag Set describes an article model that is highly prescriptive with limited choices to support model-driven authoring and editing tools.
Scope
By design, this is a model for journal articles, such as the typical research article found in an STM journal, and not a model for complete journals. This Tag Set does not include an overarching model for a collection of articles. In addition, the following journal material is not described by this Tag Set:
  • Company, product, or service display advertising
  • Job search or classified advertising
  • Calendars, meeting schedules, and conference announcements (except as these can be tagged as ordinary articles or as sections within articles)
  • Material specific to an individual journal, such as Author Guidelines, Policy and Scope statements, editorial or advisory boards, detailed indicia, etc.
Article Structural Overview
The Article Authoring Tag Set defines a document that is a top-level component of a journal such as an article, a book or product review, or a letter to the editor. Each such document is composed of one or more parts; if there is more than one part, they must appear in the following order:
  • Processing Metadata (optional). The metadata that concerns the XML file rather than the contents of the article.
  • Front matter (required). The article front matter contains the metadata for the article (also called article header information), for example, the article title, the names of the contributor(s), and the abstract. This is not textual front matter as appears in books, rather this is bibliographic information about the article.
  • Body of the article (required). The body of the article is the main textual and graphic content of the article. This usually consists of paragraphs and sections, which may themselves contain figures, tables, sidebars (boxed text), etc.
  • Back matter for the article (optional). If present, the article back matter contains information that is ancillary to the main text, such as a glossary, appendix, or list of cited references.
Tag Sets Developed from the Suite
XML schemas (DTDs, XSDs, and RNGs) are provided for 2 different variations of the Authoring Tag Set:
  • Authoring Tag Set using XHTML tables and MathML 2.0
  • Authoring Tag Set using XHTML tables and MathML 3.0
This Authoring Tag Set is one of several created from the Suite. Information about the other Tag Sets may be found at the following site: https://jats.nlm.nih.gov
Acknowledgments
Many people and organizations have contributed to the development, maintenance, and documentation of JATS. In naming some in these Acknowledgments we want to make it clear that any omissions are accidents of history, and we appreciate all contributions.
We thank bmj.com, Molecular Biology of the Cell, and The Proceedings of the National Academy of Sciences of the U.S.A. for providing many of the sample articles used in this Tag Library.
We thank AIP, John Benjamin Publishing Company, and Tony Graham of Antenna House for examples used throughout the documentation.
We thank the members of the NLM DTD working group:
  • Jeff Beck, Moderator, National Library of Medicine
  • Alex Brown. Griffin Brown
  • Mark Doyle. American Physical Society
  • Beth Friedman. Data Conversion Laboratory
  • Linda Good. Cadmus Communications
  • Kathryn Henniss. HighWire Press
  • Laura Kelly. National Library of Medicine
  • Debbie Lapeyre, Tag Set Secretariat. Mulberry Technologies, Inc.
  • Nikos Markantonatos. Atypon Systems, Inc.
  • John Meyer. Portico
  • Jules Milner-Brage. HighWire Press
  • Tom Mowlam. BioMed Central
  • Evan Owens. Portico
  • Bruce Rosenblum. Inera, Inc.
  • B. Tommie Usdin. Mulberry Technologies, Inc.
We thank the past and current members of the NISO JATS Committee; now the NISO JATS Standing Committee:
  • Ardie Bausenbach. Library of Congress
  • Jeffrey Beck. National Library of Medicine (NLM)
  • Brooke Begin. Silverchair Information Systems
  • Franziska Buehring. De Gruyter
  • Paul Donohoe. Macmillan Science and Education
  • Thomas Dowling. OhioLINK
  • Mark Doyle. American Physical Society (APS)
  • Patricia Feeney. Crossref
  • Gustavo Fonseca. SciELO
  • Kevin Hawkins. University of North Texas Libraries
  • Kathryn Henniss. HighWire Press
  • Diane Hillmann. Metadata Management Associates
  • Debbie Lapeyre. Mulberry Technologies, Inc.
  • Vincent Lizzi. Taylor & Francis Group
  • Nikos Markantonatos. Atypon
  • Mary McRae. Orbis Technologies
  • John Meyer. ITHAKA/JSTOR/Portico
  • Nick Nunes. HighWire Press
  • Evan Owens. Evan Owens
  • Laura Randall. National Library of Medicine (NLM)
  • Kennett Rawson. IEEE
  • Bruce Rosenblum. Inera Inc.
  • Kathleen Sheedy. American Psychological Association (APA)
  • Soichi Tokizane, Aichi University
  • B. Tommie Usdin, Mulberry Technologies, Inc.
  • Alex Wade, Microsoft Corporation
We thank OASIS, for use of the OASIS/CALS table model, the MathML committee for use of MathML, NISO for hosting this work, and the National Library of Medicine for hosting the non-normative but absolutely essential user documentation that makes JATS work.