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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 ...
Data Schema: For modeling the Thing's data that can be exchanged, the concept of JSON schema [11] is embedded in the Thing Description. Bindings: The binding templates define the specific protocol and serialization method for the properties, actions, and events of the Thing.
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.
XML schema: DOM, SAX, XQuery, XPath — FHIR: Health Level 7: REST basics Yes Fast Healthcare Interoperability Resources: Yes Yes Yes Yes Hapi for FHIR [4] JSON, XML, Turtle: No Ion: Amazon: JSON: No The Amazon Ion Specification: Yes Yes No Ion schema: C, C#, Go, Java, JavaScript, Python, Rust — Java serialization Oracle Corporation — Yes ...
Thing Descriptions promote JSON by offering both human- and machine-readable (and understandable) JSON about a Thing, such as its title, ID, descriptions, and more. Additionally, a Thing Description outlines all available actions, events, and properties of a Thing, as well as the security mechanisms required to access them.
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.
Schema.org is a reference website that publishes documentation and guidelines for using structured data mark-up on web-pages (called microdata).Its main objective is to standardize HTML tags to be used by webmasters for creating rich results (displayed as visual data or infographic tables on search engine results) about a certain topic of interest. [2]
Common examples of DDL statements include CREATE, ALTER, and DROP. If you see a .ddl file, that means the file contains a statement to create a table. Oracle SQL Developer contains the ability to export from an ERD generated with Data Modeler to either a .sql file or a .ddl file.