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While JSON provides a syntactic framework for data interchange, unambiguous data interchange also requires agreement between producer and consumer on the semantics of specific use of the JSON syntax. [25] One example of where such an agreement is necessary is the serialization of data types that are not part of the JSON standard, for example ...
For example, PKIX uses such notation in RFC 5912. With such notation (constraints on parameterized types using information object sets), generic ASN.1 tools/libraries can automatically encode/decode/resolve references within a document. ^ The primary format is binary, a json encoder is available. [10]
Concatenated JSON isn't a new format, it's simply a name for streaming multiple JSON objects without any delimiters. The advantage of this format is that it can handle JSON objects that have been formatted with embedded newline characters, e.g., pretty-printed for human readability. For example, these two inputs are both valid and produce the ...
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 or JavaScript Object Notation, is an open standard format that uses human-readable text to transmit data objects. JSON has been popularized by web services developed utilizing REST principles. Databases such as MongoDB and Couchbase store data natively in JSON format, leveraging the pros of semi-structured data architecture.
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
[4]: 114 A DataFrame is a 2-dimensional data structure of rows and columns, similar to a spreadsheet, and analogous to a Python dictionary mapping column names (keys) to Series (values), with each Series sharing an index. [4]: 115 DataFrames can be concatenated together or "merged" on columns or indices in a manner similar to joins in SQL.
The description format has the same purpose for JSON-WSP as WSDL has for SOAP or IDL for CORBA, which is to describe the types and methods used in a given service. It also describes inter-type relations (i.e. nested types) and defines which types are expected as method arguments and which types the user can expect to receive as method return ...