As in all main terrestrial DTV Systems, the Brazilian middleware, named Ginga, supports both declarative applications (through its presentation, or declarative, environment Ginga-NCL) and procedural applications (through its execution, or procedural, environment Ginga-J). Since hybrid applications are common, either type of Ginga application may make use of facilities of both presentation and execution application environments. This paper focuses on the presentation environment Ginga-NCL. The main Brazilian inovations are then presented, regarding the Ginga architecture, the declarative NCL language specification, the editing commands for live application production, and the transport data structure.

Nested Context Language (NCL) is the declarative language of the Brazilian Terrestrial Digital TV System. NCL is part of ISDB (International Standard for Digital Broadcasting) standards and also the ITU-T Recommendation H.761 for IPTV services. This paper presents, discusses, and illustrates the NCL hierarchical control model for multiple exhibition device support. Based on this model, multiple devices are orchestrated to run a DTV application in cooperation. Two types of multiple device exhibitions are distinguished. Those where the same content is shown in a set of devices under a unique control, and those where content is under each individual device control, working completely independent. In this last case, depending on viewer interactions, the resulting presented content can differ from a device to another. Examples of NCL applications using both options are presented and discussed.

Machine Learning (ML) has become essential in several industries. In Computational Science and Engineering (CSE), the complexity of the ML lifecycle comes from the large variety of data, scientists' expertise, tools, and workflows. If data are not tracked properly during the lifecycle, it becomes unfeasible to recreate a ML model from scratch or to explain to stakeholders how it was created. The main limitation of provenance tracking solutions is that they cannot cope with provenance capture and integration of domain and ML data processed in the multiple workflows in the lifecycle, while keeping the provenance capture overhead low. To handle this problem, in this paper we contribute with a detailed characterization of provenance data in the ML lifecycle in CSE; a new provenance data representation, called PROV-ML, built on top of W3C PROV and ML Schema; and extensions to a system that tracks provenance from multiple workflows to address the characteristics of ML and CSE, and to allow for provenance queries with a standard vocabulary. We show a practical use in a real case in the O&G industry, along with its evaluation using 48 GPUs in parallel.Index Terms-Machine Learning Lifecycle, Workflow Provenance, Computational Science and Engineering (ii) PROV-ML: a new data representation, which combines W3C PROV [18] with W3C ML Schema [19], for prove-R. Souza et al. Provenance Data in the Machine Learning Lifecycle in Computational Science and Engineering.

As in all main terrestrial DTV Systems, the Brazilian middleware, named Ginga, supports both declarative applications (through its presentation, or declarative, environment Ginga-NCL) and procedural applications (through its execution, or procedural, environment Ginga-J). Since hybrid applications are common, either type of Ginga application may make use of facilities of both presentation and execution application environments. This paper focuses on the presentation environment Ginga-NCL. The main Brazilian inovations are then presented, regarding the Ginga architecture, the declarative NCL language specification, the editing commands for live application production, and the transport data structure.

In some hypermedia system applications, like interactive digital TV applications, authoring and presentation of documents may have to be done concomitantly. This is the case of live programs, where not only some contents are not known a priori, but also some temporal and spatial relationships, among program media objects, may have to be established after the unknown content definition. This paper proposes a method for hypermedia document live editing, preserving not only the presentation semantics but also the logical structure semantics defined by an author. To validate this proposal, an implementation has been done for the Brazilian Digital TV System, which is also presented.