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Goals and Non-Goals

This document defines the purpose of the Message Format Working Group (MFWG) and informs the decisions about the scope and the priorities of its efforts.

Goals

The primary task of the MFWG is to develop an industry standard for the representation of localizable message strings. The design goals are listed below.

  1. Express grammatical features, such as plurals, genders, and inflections.

  2. Express other variance in translation, due to linguistic and regional features, the presentation media, context, circumstance, and other factors.

  3. Express formattable data, such as numbers, dates, currencies, and units.

  4. Represent structured data alongside translations, such as markup, comments, and metadata.

  5. Be capable of localization roundtrip.

  6. Enable the creation of implementations, frameworks and tools building on top of the standard, manifesting different ideas and programming paradigms, and optimized for different uses and audiences.

Deliverables

  1. A formal definition of the canonical data model for representing localizable message strings.

  2. A formal definition of the canonical syntax for representing the data model, with well defined rules for handling text, special characters, escape sequences, whitespace, markup, as well as parsing errors.

  3. A specification for a one-to-one mapping between the data model and XLIFF.

  4. A specification for resolving translations at runtime, including interpolated data types and runtime errors.

  5. A conformance test suite for parsing and formatting messages.

Non-Goals

The following is a list of potential goals which are explicitly excluded from the scope of the MFWG.

  1. Design a general interchange format for storing and transferring translations. Instead, ensure compatibility with the existing interchange formats.

  2. Support all grammatical features of all languages. Instead, focus on features most commonly encountered in user interfaces, textual, graphical and spoken ones alike.

  3. Create an automated engine capable of transforming parts of speech in a grammatically-correct fashion. Instead, allow interfacing with such automatic and non-automatic engines from within the data model.

  4. Create optimized and efficient implementations of the standard. Instead, create specifications, compliance test suites, recommendations and good practices to support implementors.

  5. Build a framework for localizing software. Instead, design the standard as a building block to be used by third parties to create localization frameworks.