JSON Schema Statistical Tree Compression for Smaller Data Payloads
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Solution Overview
Problem
JSON documents are large due to text-based encoding and repeated key names, and existing compression techniques do not effectively utilize the well-defined structure of JSON data, leading to suboptimal compression.
Innovation Solution
A method using a statistical tree representing the JSON Schema to encode JSON data, where each path in the tree is optimized to represent elements, enumerations, and attributes with a single bit, leveraging the inherent structure of JSON documents for efficient compression.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If JSON data is encoded using text-based encoding with repeated key names, then the data is human-readable and language-independent, but the document size becomes large
Solution Approach 1:
The patent segments the JSON document into two separate components: a schema definition that describes the structure (keys, types, constraints) and actual data values. By separating the structural metadata from the data content, the patent eliminates repeated key names in the data portion, reducing document size while maintaining readability through the schema.
Solution Approach 2:
The patent extracts the structural information (keys, data types, constraints) into a separate JSON Schema definition, removing redundant structural repetition from the main data document. This extraction allows the data to be represented more compactly while the schema provides the necessary structural context for interpretation.
2Weight of stationary object
If existing compression techniques are used on JSON data, then some size reduction is achieved, but the well-defined structure of JSON is not effectively utilized
Solution Approach 1:
The patent changes the representation parameters of JSON data by introducing a schema-based encoding system. Instead of compressing the text directly, it transforms the data into a schema-constrained format where structural parameters are defined once in the schema and referenced efficiently in the data, achieving better compression ratios.
Solution Approach 2:
The patent performs preliminary structuring of JSON data by defining the schema beforehand. This preliminary action organizes the data structure, types, and constraints in advance, enabling more efficient compression during the encoding phase by eliminating the need to repeatedly encode structural information.
3Weight of stationary object
If JSON data is transposed and grouped by key instances or converted to binary form, then document size is reduced, but the inherent structure is not optimally utilized and complexity increases
Solution Approach 1:
The patent creates a universal schema-based encoding system that works across different JSON data structures and types. The schema definition serves multiple functions: validating data structure, enabling compression, and facilitating efficient decoding, making the system versatile for various JSON applications without increasing operational complexity.
Solution Approach 2:
The patent introduces JSON Schema as an intermediary layer between the raw JSON data and the compression/decoding process. This intermediary schema definition captures the structural essence of the data, enabling efficient processing while maintaining the ease of operation through standardized schema validation and interpretation mechanisms.
Data Source
AI summary
A method for encoding and decoding a javascript object notation (JSON) document utilizing a statistical tree representing a JSON Schema. The encoded statistical tree may be optimized.