Federated Query Platform for Integrated Public and Private Data Access
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Solution Overview
Problem
Conventional techniques are inadequate for managing large-scale data access, particularly in integrating public and privately-accessible datasets, as they require expert knowledge of programming languages, databases, and data science topics, and lack the ability to handle disparate data resources effectively.
Innovation Solution
A platform utilizing federated query generation and schema rewriting optimization to provide integrated access to public and privately-accessible datasets, enabling users to query and retrieve data from various sources without needing extensive technical expertise, by converting queries into a unified format and optimizing them for execution across different data storage facilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional techniques are used for data access, then data retrieval is possible, but expert knowledge of programming languages and databases is required
Solution Approach 1:
The patent introduces a natural language processing intermediary layer that translates user-friendly natural language queries into database-specific query languages. This mediator handles the complexity of database interactions, authentication, and data retrieval, while users only need to provide simple natural language questions, eliminating the need for expert knowledge of programming languages and database schemas.
2Adaptability or versatility
If integrated access to multiple data sources is implemented, then data availability increases, but system complexity increases
Solution Approach 1:
The patent implements a universal natural language processing interface that can interact with multiple different data sources including public datasets, private databases, and third-party APIs through a single unified system. The system automatically adapts to different data sources by translating natural language queries into appropriate query languages and handling source-specific authentication, providing multi-functional access without requiring separate systems for each data source.
3Reliability
If secure access to private datasets is implemented, then data security is improved, but access control complexity increases
Solution Approach 1:
The patent implements automated authentication and access control mechanisms where the system itself manages security credentials, token generation, and permission verification. The natural language processing interface automatically handles authentication with private data sources, manages session tokens, and enforces access controls without requiring users to manually configure security settings or understand authentication protocols, thereby maintaining high security while keeping the interface simple for users.
Data Source
AI summary
Various techniques are described for platform management of integrated access of public and privately-accessible datasets utilizing federated query generation and query schema rewriting optimization, including receiving at a dataset access platform a query formatted according to a first data schema, generating a copy of the query, saving the query and the copy to a datastore, parsing the copy of the query in the first schema using an inference engine, determining whether the query comprises data associated with an access control condition associated with accessing the dataset, the access control condition being configured to indicate whether the query is permitted to access the dataset, and rewriting, using a proxy server, the copy of the query in a second schema, and optimizing the rewriting by identifying a database engine to execute the query and including other data converted into another triple associated with an attribute of the query.