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JSONiq [11] is a query and transformation language for JSON. XPath 3.1 [12] is an expression language that allows the processing of values conforming to the XDM [13] data model. The version 3.1 of XPath supports JSON as well as XML. jq is like sed for JSON data – it can be used to slice and filter and map and transform structured data.
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-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]
yangson is a Python 3 library for working with JSON encoded configuration and state data modeled using the YANG data modeling language. YANG Tools is an OpenDaylight Project toolset written in Java Yang-Explorer - is a pyang-based Yang Browser and RPC Builder Application
Line-delimited JSON works very well with traditional line-oriented tools. Concatenated JSON works with pretty-printed JSON but requires more effort and complexity to parse. It doesn't work well with traditional line-oriented tools. Concatenated JSON streaming is a superset of line-delimited JSON streaming.
A semantic triple, or RDF triple or simply triple, is the atomic data entity in the Resource Description Framework (RDF) data model. [1] As its name indicates, a triple is a sequence of three entities that codifies a statement about semantic data in the form of subject–predicate–object expressions (e.g., "Bob is 35", or "Bob knows John").
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.
Numeric literals in Python are of the normal sort, e.g. 0, -1, 3.4, 3.5e-8. Python has arbitrary-length integers and automatically increases their storage size as necessary. Prior to Python 3, there were two kinds of integral numbers: traditional fixed size integers and "long" integers of arbitrary size.