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Arbitrary-length key/value pairs with end-marker Structured Data eXchange Formats (SDXF) Big-endian signed 24-bit or 32-bit integer Big-endian IEEE double Either UTF-8 or ISO 8859-1 encoded List of elements with identical ID and size, preceded by array header with int16 length Chunks can contain other chunks to arbitrary depth. Thrift
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 ...
As a superset of JSON, Ion includes the following data types null: An empty value; bool: Boolean values; string: Unicode text literals; list: Ordered heterogeneous collection of Ion values; struct: Unordered collection of key/value pairs; The nebulous JSON 'number' type is strictly defined in Ion to be one of int: Signed integers of arbitrary size
Many field values may contain a quality (q) key-value pair separated by equals sign, specifying a weight to use in content negotiation. [9] For example, a browser may indicate that it accepts information in German or English, with German as preferred by setting the q value for de higher than that of en, as follows: Accept-Language: de; q=1.0 ...
Example of a web form with name-value pairs. A name–value pair, also called an attribute–value pair, key–value pair, or field–value pair, is a fundamental data representation in computing systems and applications. Designers often desire an open-ended data structure that allows for future extension without modifying existing code or data.
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.
The terms schema matching and mapping are often used interchangeably for a database process. For this article, we differentiate the two as follows: schema matching is the process of identifying that two objects are semantically related (scope of this article) while mapping refers to the transformations between the objects.
MessagePack is more compact than JSON, but imposes limitations on array and integer sizes.On the other hand, it allows binary data and non-UTF-8 encoded strings. In JSON, map keys have to be strings, but in MessagePack there is no such limitation and any type can be a map key, including types like maps and arrays, and, like YAML, numbers.