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JSON Schema specifies a JSON-based format to define the structure of JSON data for validation, documentation, and interaction control. It provides a contract for the JSON data required by a given application and how that data can be modified. [29] JSON Schema is based on the concepts from XML Schema (XSD) but is JSON-based. As in XSD, the same ...
JSON: No Smile Format Specification: Yes No Yes Partial (JSON Schema Proposal, other JSON schemas/IDLs) Partial (via JSON APIs implemented with Smile backend, on Jackson, Python) — SOAP: W3C: XML: Yes W3C Recommendations: SOAP/1.1 SOAP/1.2: Partial (Efficient XML Interchange, Binary XML, Fast Infoset, MTOM, XSD base64 data) Yes Built-in id ...
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 ...
Every [item] in the data must be [an integer between 0 and 100] and must conform to [the standard format for numeric ranges]. Generate JSON schema to validate. [Input data].
The W3C's accompanying XML Schema ... and to define the structure of JSON data for validation, documentation, ... machine-readable, data format standards;
It was proposed at the 2012 RDF Validation Workshop [3] as a high-level, concise language for RDF validation. The shapes can be defined in a human-friendly compact syntax called ShExC or using any RDF serialization formats like JSON-LD or Turtle. ShEx expressions can be used both to describe RDF and to automatically check the conformance of RDF ...
JSON-LD (JavaScript Object Notation for Linked Data) is a method of encoding linked data using JSON. One goal for JSON-LD was to require as little effort as possible from developers to transform their existing JSON to JSON-LD. [1] JSON-LD allows data to be serialized in a way that is similar to traditional JSON. [2]
In some domains, a few dozen different source and target schema (proprietary data formats) may exist. An "exchange" or "interchange format" is often developed for a single domain, and then necessary routines (mappings) are written to (indirectly) transform/translate each and every source schema to each and every target schema by using the interchange format as an intermediate step.