ORD Entity Type Metadata for Faster API Discovery
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing systems struggle to efficiently discover and integrate application programming interfaces (APIs) due to the lack of standardized methods for exposing metadata, leading to difficulties in building extensions and integrations across heterogeneous landscapes.
Innovation Solution
An open resource discovery (ORD) protocol that standardizes entity type descriptions using machine-readable formats, enabling automated processes to discover and connect APIs across different protocols, providing a centralized portal for API cataloging and harmonizing taxonomy and interfaces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If standardized entity type descriptions are implemented, then API discovery speed is improved, but system complexity increases
Solution Approach 1:
The patent changes the parameter of metadata representation from unstandardized formats to standardized entity type descriptions with specific parameters (identifier, reference, description, data model structure). This standardization enables automated processing and faster discovery while managing complexity through consistent parameter definitions.
Solution Approach 2:
The patent introduces entity types as intermediary objects that mediate between APIs and event information. These entity types serve as a standardized layer that simplifies discovery by providing a common interface, while the underlying complexity of different APIs and protocols is abstracted away.
2Extent of automation
If machine-readable formats are used for entity type descriptions, then automation capability is improved, but information loss risk increases
Solution Approach 1:
The patent replaces manual documentation reading and expert consultation with machine-readable entity type descriptions. This substitution enables automated discovery processes while the comprehensive parameters (identifier, reference, description, data model structure) ensure that no critical information is lost in the transition from human-readable to machine-readable formats.
3Manufacturing precision
If comprehensive metadata is exposed, then integration accuracy is improved, but data transmission volume increases
Solution Approach 1:
The patent extracts only the essential metadata parameters needed for API discovery and integration (identifier, reference, description, data model structure) while omitting redundant information. This extraction maintains integration accuracy by including all necessary information while reducing data transmission volume by excluding unnecessary details.
Data Source
AI summary
The disclosure generally describes methods, software, and systems for open resource discovery protocol describing entity types. An identifier of a first entity type is received. The first entity type defines a relation between an application programming interface (API) and event information. A reference for the first entity type is generated based on the identifier of the first entity type. The reference links the first entity type to the API. A description of the first entity type is provided for storage using the reference for the first entity type. the description includes a structure of an underlying data model. A request to provide the first entity type based on the description of the first entity type is received. The first entity type is provided using an exposed API and the reference for the first entity type.