Relationship Data Structure for Heterogeneous Object Discovery
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Solution Overview
Problem
The challenge in electronic discovery processes is managing and accessing vast amounts of electronic data across distributed systems, particularly in litigation, where archive files and backup tapes contain relevant information but are not designed for flexible searching, leading to slow access and compliance issues due to the complexity and volume of data.
Innovation Solution
A software system that identifies and manages relationships among various types of objects, including transactional data, documents, and source code, using APIs to determine related objects and populate a relationship data structure, facilitating legal hold processes, document collection, and case management by providing a central entry point for legal discovery and supporting different data types across various repositories.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is stored in archive files or backup tapes, then data retention and compliance are improved, but data accessibility and search flexibility deteriorate
Solution Approach 1:
The patent introduces an intermediary system that sits between the archive/backup storage and the users/search systems. This intermediary maintains metadata indexes and relationship data structures that enable fast searching and access to archived data without requiring direct access to the underlying archive files or backup tapes, thus preserving data retention while improving accessibility
Solution Approach 2:
The patent creates copies of data relationships and metadata information in the form of relationship data structures and indexes. These copies allow rapid searching and access to archived data without moving or modifying the actual archived data, maintaining both retention and accessibility
2Reliability
If comprehensive electronic data is preserved for litigation, then compliance and legal readiness are improved, but data management complexity and storage requirements worsen
Solution Approach 1:
The patent segments data management into distinct components: active data, archived data, and backup data. Each segment is managed separately with appropriate tools and methods, reducing overall complexity while ensuring comprehensive compliance coverage across all data types
Solution Approach 2:
The patent creates a universal relationship data structure and search system that can handle multiple data types (active, archived, backup) through a common interface and methodology, simplifying management complexity while maintaining comprehensive compliance
3Measurement precision
If relationship data structures are populated using multiple object type APIs, then relationship identification accuracy is improved, but processing time and computational resources worsen
Solution Approach 1:
The patent performs preliminary actions by pre-establishing relationship data structures and metadata indexes during normal data operations and archiving processes. This preliminary population of relationship information enables rapid querying and analysis without requiring extensive processing at the time of legal discovery, thus improving accuracy while reducing processing time
Solution Approach 2:
The patent implements a staged approach to population relationship data structures, using at least one object type API initially and optionally expanding to multiple APIs based on specific needs. This partial action approach balances processing requirements with relationship identification accuracy
Data Source
AI summary
Software for managing relationships between heterogeneous objects is operable to identify a target object. The software automatically determines related objects using at least one object type application programming interface (API) for an object type associated with the target object. The software is further operable to populate a relationship data structure based on the determined relationships. The software can then provide the relationship data structure to a requesting module.