W3C

The Distributed Tracing Working Group has published Trace Context as a W3C Recommendation. This specification defines standard HTTP headers and a value format to propagate context information that enables distributed tracing scenarios. The specification standardizes how context information is sent and modified between services. Context information uniquely identifies individual requests in a distributed system and also defines a means to add and propagate provider-specific context information.

The Accessible Platform Architectures (APA) Working Group with the Personalization Semantics Task Force has published an updated Personalization Semantics Content Module 1.0 specification for wide review. For a short introduction to personalization and the related documents, see the Personalization Overview. The Working Group particularly requests review of section 3.1 action. Please send any comments by 10 March 2020.

The W3C Dataset Exchange Working Group has published Data Catalog Vocabulary (DCAT) – Version 2 as a W3C Recommendation. DCAT defines an RDF vocabulary designed to facilitate interoperability between data catalogs published on the Web. The specification defines the schema and provides examples for its use. Version 2 extends the original DCAT standard in line with community practice while supporting diverse approaches to data description and dataset exchange.

The Media Working Group has published First Public Working Drafts of three specifications that enhance media user experiences on the Web:

• Media Capabilities defines APIs to allow websites to make an optimal decision for decoding, encoding, and rendering when picking media content for the user.
• Picture-in-Picture allows websites to create a floating video window always on top of other windows so that users may continue consuming media while they interact with other content sites or applications on their device.
• The Media Session Standard enables web developers to show customized media metadata on platform UI, customize available platform media controls, and access platform media keys such as hardware keys found on keyboards, headsets, remote controls, and software keys found in notification areas and on lock screens of mobile devices.

The Web of Things Working Group has published two Proposed Recommendations:

• Web of Things (WoT) Architecture
• Web of Things (WoT) Thing Description

WoT Architecture describes a formal model and a common representation for a WoT Thing Description. A Thing Description describes the metadata and interfaces of Things, where a Thing is an abstraction of a physical or virtual entity that provides interactions to and participates in the Web of Things. Thing Descriptions provide a set of interactions based on a small vocabulary that makes it possible both to integrate diverse devices and to allow diverse applications to interoperate.

Comments are welcome through 27 February 2020.

The Timed Text (TT) Working Group invites implementation of its updated Candidate Recommendation of Timed Text Markup Language 2 (TTML2) (2nd Edition). This document specifies the Second Edition of the Timed Text Markup Language (TTML), Version 2, also known as TTML2 (2e), in terms of a vocabulary and semantics thereof. The Timed Text Markup Language is a content type that represents timed text media for the purpose of interchange among authoring systems. Timed text is textual information that is intrinsically or extrinsically associated with timing information. It is intended to be used for the purpose of transcoding or exchanging timed text information among legacy distribution content formats presently in use for subtitling and captioning functions.

Comments are welcome by 25 February 2020.

W3C announced today a Workshop on Web & Machine Learning, 24-25 March 2020, in Berlin, Germany. The event is hosted by Microsoft.

The primary goal of the workshop is to bring together providers of Machine Learning tools and frameworks with Web platform practitioners to enrich the Open Web Platform with better foundations for machine learning.

The secondary goals of the workshop are as follows:

• Understand how machine learning fits into the Web technology stack,
• Understand how browser-based machine learning fits into the machine learning ecosystem,
• Explore the impact of machine learning technologies on Web browsers and Web applications,
• Evaluate the opportunities for standardization around machine learning APIs and formats.

Expected topics of discussion include:

• Dedicated machine learning APIs for browsers as explored by the Machine Learning for the Web Community Group
• Integration of browser-provided data sources in machine learning workflows
• Layering and interoperability of machine learning APIs with other computing APIs (e.g. WebGPU, WebAssembly)
• Domain-specific machine learning APIs
• Interchange format for machine learning models on the Web
• Client- and cloud-based machine learning interactions
• On-device machine learning training in browsers
• Risks and benefits of browser-based machine learning on privacy, security, accessibility
• Using machine learning primitives to help improve accessibility of Web pages and applications
• Machine learning frameworks for the Web
• Machine learning hardware accelerators

Attendance is free for all invited participants and is open to the public, whether or not W3C members. For more information on the workshop, please see the workshop details and submission instructions.

Registration is available online due by 21 February 2020.