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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 ...
^ ASN.1 has X.681 (Information Object System), X.682 (Constraints), and X.683 (Parameterization) that allow for the precise specification of open types where the types of values can be identified by integers, by OIDs, etc. OIDs are a standard format for globally unique identifiers, as well as a standard notation ("absolute reference") for ...
[4] [5] The topmost element in the structure must be of type BSON object and contains 1 or more elements, where an element consists of a field name, a type, and a value. Field names are strings. Types include: Unicode string (using the UTF-8 encoding) 32-bit integer; 64-bit integer; double (64-bit IEEE 754 floating point number, including NaN/Inf)
Validation metadata include data type, range of permissible values or membership in a set of values, regular expression match, default value, and whether the value is permitted to be null. In EAV systems representing classes with substructure, the validation metadata will also record what class, if any, a given attribute belongs to.
This could be modeled in an object-oriented implementation by a "Person object" with an attribute/field to hold each data item that the entry comprises: the person's name, a list of phone numbers, and a list of addresses. The list of phone numbers would itself contain "PhoneNumber objects" and so on.
[4] [5] It was described as being "like sed for JSON data". [6] Support for regular expressions was added in jq version 1.5. A "wrapper" program for jq named yq adds support for YAML, XML and TOML. It was first released in 2017. [7] The Go implementation, gojq, was initially released in 2019. [8] gojq notably extends jq to include support for YAML.
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.
JSON streaming comprises communications protocols to delimit JSON objects built upon lower-level stream-oriented protocols (such as TCP), that ensures individual JSON objects are recognized, when the server and clients use the same one (e.g. implicitly coded in). This is necessary as JSON is a non-concatenative protocol (the concatenation of ...