Hierarchical Data Models for Archived Storage Retrieval
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Solution Overview
Problem
Current data retrieval processes from archived and live databases are cumbersome and complex, particularly when dealing with data privacy protection requirements, as they often involve decentralized storage and restricted access, making it difficult to retrieve and present data in compliance with regulations like GDPR.
Innovation Solution
A computer-implemented method using hierarchical data models to access and combine data from archived and live storage locations, allowing for centralized retrieval and presentation of data, including the generation of merged models for data objects based on specific purposes, and utilizing information retrieval frameworks to ensure compliance with data protection policies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is stored in decentralized archived and live databases, then data can be stored in various locations for flexibility, but data retrieval becomes cumbersome and complex
Solution Approach 1:
The patent introduces an information retrieval framework as an intermediary layer between the decentralized databases and the user. This framework generates hierarchical data models that abstract the complexity of distributed storage, allowing users to query data without needing to understand its physical location across multiple archived and live databases.
Solution Approach 2:
The patent segments the decentralized data storage system into organized hierarchical data models with multiple levels and nodes. Each node represents a specific data element or collection, and the hierarchical structure allows systematic navigation and retrieval of data from distributed locations through a unified interface.
2Reliability
If data is archived in separate storage locations, then data retention and privacy protection are improved, but access and retrieval of archived data become restricted and difficult
Solution Approach 1:
The information retrieval framework acts as a mediator that respects privacy restrictions while enabling authorized access. It generates hierarchical data models that incorporate access control information, allowing the system to retrieve archived data when appropriate permissions are granted without compromising privacy protection for restricted data.
Solution Approach 2:
The system performs preliminary actions by pre-generating hierarchical data models that encode access permissions and data location information. These models are prepared in advance, enabling the system to quickly determine whether archived data can be accessed and from where, without requiring complex real-time authorization checks during data retrieval.
3Productivity
If multiple storage locations are used for archived and live data, then data availability is improved, but the complexity of managing and retrieving data increases
Solution Approach 1:
The hierarchical data model structure serves multiple functions simultaneously: it tracks data location across archived and live databases, manages access permissions, organizes data in a navigable hierarchy, and enables efficient retrieval. This universal structure reduces the need for separate management mechanisms for each storage location.
Solution Approach 2:
The information retrieval framework provides a universal interface that hides the complexity of managing multiple storage locations. Users interact with the unified hierarchical model rather than dealing with individual archived and live database systems, thereby maintaining data availability across multiple locations while simplifying management operations.
Data Source
AI summary
A method, a system, and a computer program product for retrieving data from an archived data storage. A query requiring access to data stored in at least one storage location in the plurality of storage locations is received. Based on the received query, at least one first storage location storing the data is determined. One or more hierarchical data models for accessing data stored in the first storage location is generated. The hierarchical data models include a plurality of nodes storing at least a portion in a plurality of portions of the data stored in the first storage location. Using the generated hierarchical data models, a first data responsive to the query is selected and combined with at least a second data stored in at least another storage location in the plurality of storage locations. The combined first data and the second data are retrieved.