The first of a three part series, the subsequent posts cover freeform and mixed use scenarios.
JSON Schema allows strict definitions, including structure, data types, length of data, and content restrictions. The elements permitted can be limited to those defined, and rules for combinations of elements can be specified.
This combination of mechanisms allows JSON content to be very crisply defined, validation to be thorough, and error recognition to be succinct.
When defining message exchanges for systems such as financial transactions, the ability to provide a well structured, completely predictable, and completely machine processing capable content definition is required.
A strict schema typically has the following characteristics,
- The additionalProperties constraint is set to false to disallow content that is not explicitly specified. Alternatively, the patternProperties constraint can be used to allow some flexibility, but with predictable property names.
- Properties will have type definitions that have content checking appropriate for machine processing. This can include length restrictions, count limit, enumeration of allowed values, and/or a regular expression for content value verification.
The processing system accepting content to process the schema can have additional validation steps including size checking for messages or limiting character encodings accepted.
Standards that include JSON representations for persistent data formats, message exchanges, or similar uses, often include interoperability requirements. Some standards organizations provide test suites or verification programs which allow independent validation of compliance to their specifications. Using constraints in the JSON Schema allows interoperability to be expressed in as fine a grain as desired.
In the next two articles, freeform and mixed scenarios are discussed.
JSON Support in Databases Growing Freeform Schema Definitions