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JSON-LD is designed around the concept of a "context" to provide additional mappings from JSON to an RDF model. The context links object properties in a JSON document to concepts in an ontology. In order to map the JSON-LD syntax to RDF, JSON-LD allows values to be coerced to a specified type or to be tagged with a language.
Also supports indexing of RDF-Turtle, RDF-N-Triples, RDF-XML, JSON-LD, and mapping and generation of relations (SQL tables or RDF graphs) from numerous document types including CSV, XML, and JSON. May be deployed as a local or embedded instance (as used in the NEPOMUK Semantic Desktop), a one-instance network server, or a shared-nothing elastic ...
JSON Pointer (RFC 6901), or alternately, JSONPath, JPath, JSPON, json:select(); and JSON-LD: Partial (JSON Schema Proposal, ASN.1 with JER, Kwalify Archived 2021-08-12 at the Wayback Machine, Rx, JSON-LD: Partial (Clarinet, JSONQuery / RQL, JSONPath), JSON-LD: No MessagePack: Sadayuki Furuhashi JSON (loosely) No MessagePack format specification ...
Compared to the basic model defined here, the NGSI-LD meta-model adds a formal definition of basic categories (entity, relation, property) on the basis of semantic webstandards (OWL, RDFS, RDF), which makes it possible to convert all data represented in NGSI-LD into RDF datasets, through JSON-LD serialization.
In 2015, [15] Google began supporting the JSON-LD format, and as of September, 2017 recommended using JSON-LD for structured data whenever possible. [16] [17] Despite the advantages of using Schema.org, adoption remained limited as of 2016. A survey in 2016 of 300 US-based marketing agencies and B2C advertisers across industries showing only 17 ...
JSON-LD and RDF are two major (and semantically almost equivalent) languages in this context, primarily because they support statement reification and contextualisation which are essential properties to support the higher-order logic needed to reason about models. Model transformation is a common example of such reasoning.
The CP/LD format defines a flexible, extensible, machine readable format that links HTML5 documents with content to JSON-LD graphs for the data and semantics. [1]The Linked Document part of the standard outlines the minimal characteristics of documents, whereas the Content Profile part describes how to extend and refine rules for specific use cases.
JSON-LD opens the opportunity of context extension and enrich the Thing Description instances with additional (e.g., domain-specific) semantics such as from Schema.org. This also supports the extraction and the understanding of relevant information such as in discovery scenarios in IoT applications [ 8 ]