The purpose of this Group Report is to explain with examples the usage of NGSI-LD information model and API, as defined in GS-004 prelimAPI, and considering also some use cases from GR-002 for ICT professionals. Worked examples are provided, with code fragments made available in a public repository. No changes in the GS-004 prelimAPI specification can be introduced or proposed in this document.
This Group Specification provides additions and corrections to the GS-009 NGSI-LD API specification, based on feedback received from developers in the linked-data, internet-of-things, mobile-apps and smart-applications communities, as well as from end users and stakeholders.
This document defines a comprehensive set of evaluation indicators specially related to information and communication technologies (ICT) adoption and usage in smart cities. Firstly, it establishes an overall framework for all the indicators. Then, it specifies the name, description, classification and measurement method for each indicator.
As accelerating improvements in city services and quality of life is fundamental to the definition of a smart city ISO 37120 is intended to provide a complete set of indicators to measure progress towards a smart city.
This recommended practice specifies how the elements and attributes defined in Multimedia Framework (MPEG-21) -Part 2: Digital Item Declaration relate to the components of the conceptual model for resource aggregation defined in IEEE Std 1484.13.1-2012
This recommended practice specifies how the elements and attributes defined in the Metadata Encoding and Transmission Standard (METS) relate to the components of the conceptual model for resource aggregation defined in IEEE Std 1484.13.1(TM)-2012.
A conceptual model for interpreting externalized representations of digital aggregations of resources for learning, education, and training is defined. The conceptual model is defined as an ontology. Internal compositions and uses of digital resources are not specified nor are processing methods for resource aggregations.
This Standard defines a World Wide Web Consortium (W3C) Extensible Markup Language (XML) Schema definition language binding of the learning object metadata (LOM) data model defined in IEEE Std 1484.12.1TM-2002. The purpose of this Standard is to allow the creation of LOM instances in XML, which allows for interoperability and the exchange of LOM XML instances between various systems. This Standard uses the W3C XML Schema definition language to define the syntax and semantics of the XML encodings.
A conceptual data schema that defines the structure of a metadata instance for a learning object is specified in this standard. For this standard, a learning object is defined as any entity, digital or non-digital, that is used for learning, education, or training; a metadata instance for a learning object describes relevant characteristics of the learning object to which it applies. Such characteristics can be regrouped in general, life cycle, meta-metadata, educational, technical, educational, rights, relation, annotation, and classification categories. The conceptual data schema defined in this standard specifies the data elements of which a metadata instance for a learning object is composed and allows for linguistic diversity of both learning objects and the metadata instances that describe them. It is intended that this standard will be referenced by other standards that will define the implementation descriptions of the data schema, so that a metadata instance for a learning object can be used by a learning technology system to manage, locate, evaluate, or exchange learning objects. The intent of this standard is to specify a base schema, which can be used to build on as practice develops, for instance in order to facilitate automatic, adaptive scheduling of learning objects by software agents.
An ECMAScript application programming interface (API) for content-to-runtime-services communication is described in this standard. It is based on a current industry practice called “CMI--computer managed instruction.” This API enables the communication of information between content and a runtime service (RTS) typically provided by a learning management system (LMS) via common API services using the ECMAScript language. The purpose of this standard is to build consensus around, resolve ambiguities, and correct defects in existing specifications for an ECMA¬Script API for exchanging data between learning-related content and an LMS.
Recommendation ITU-T Y.4470 establishes artificial intelligence service exposure (AISE) for smart sustainable cities (SSCs), and provides the common characteristics and high-level requirements, reference architecture and relevant common capabilities of AISE. AISE is one of the basic supporting functional entities for SSCs, with which SSC services can use uniform reference points (exposed by AISE) to integrate and access the artificial intelligence (AI) capabilities of AI services (e.g., machine learning services for image recognition, natural language processing services and traffic prediction services). In addition, AISE can collect and open SSC data, and it supports AI services to train and supply AI capabilities in AISE in SSCs.
This document defines and establishes methodologies for a set of indicators to steer and measure the performance of city services and quality of life. It follows the principles set out in ISO 37101 and can be used in conjunction with ISO 37101 and other strategic frameworks. This document is applicable to any city, municipality or local government that undertakes to measure its performance in a comparable and verifiable manner, irrespective of size and location.