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  2. SHACL - Wikipedia

    en.wikipedia.org/wiki/SHACL

    A SHACL validation engine takes as input a graph to be validated (called data graph) and a graph containing SHACL shapes declarations (called shapes graph) and produces a validation report, also expressed as a graph. All these graphs can be represented in any Resource Description Framework (RDF) serialization formats including JSON-LD or Turtle.

  3. JSON - Wikipedia

    en.wikipedia.org/wiki/JSON

    JSON Schema specifies a JSON-based format to define the structure of JSON data for validation, ... is a subset of JSON5 used in Microsoft's Visual Studio Code: [64 ...

  4. Comparison of data-serialization formats - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_data...

    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 ...

  5. jq (programming language) - Wikipedia

    en.wikipedia.org/wiki/Jq_(programming_language)

    jq by default acts as a "stream editor" for JSON inputs, much like the sed utility can be thought of as a "stream editor" for lines of text. However jq has several other modes of operation: it can treat its input from one or more sources as lines of text; it can gather a stream of inputs from a specified source into a JSON array;

  6. JSONPath - Wikipedia

    en.wikipedia.org/wiki/JSONPath

    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.

  7. Data validation - Wikipedia

    en.wikipedia.org/wiki/Data_validation

    Data validation is intended to provide certain well-defined guarantees for fitness and consistency of data in an application or automated system. Data validation rules can be defined and designed using various methodologies, and be deployed in various contexts. [1]

  8. Laminas - Wikipedia

    en.wikipedia.org/wiki/Laminas

    Normalize and validate input sets from the web, APIs, the CLI, and more, including files. Internationalization Provide translations for your application, and filter and validate internationalized values. JSON De/Serialize JSON in PHP, including JavaScript expressions. JSON-RPC Server JSON-RPC implementation for PHP. LDAP

  9. Verification and validation - Wikipedia

    en.wikipedia.org/wiki/Verification_and_validation

    Verification is intended to check that a product, service, or system meets a set of design specifications. [6] [7] In the development phase, verification procedures involve performing special tests to model or simulate a portion, or the entirety, of a product, service, or system, then performing a review or analysis of the modeling results.