Communication Data Mapping for Electronic Discovery
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Solution Overview
Problem
Current methods for reviewing communication items in large organizations during litigation are slow and resource-intensive, making it difficult to efficiently identify relevant communication items and relationships for electronic discovery.
Innovation Solution
A system and method that generates and visualizes a people map and an evidence map using communication data, linking individuals with communication items and items with each other through metadata, to facilitate the identification and analysis of communication chains and relationships.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional search methods are used to review communication items, then the review process can be performed with simple tools, but the review speed is slow and IT resources are excessively consumed
Solution Approach 1:
The patent introduces an intermediary indexing system that creates a mapping between communication items and their metadata (people, dates, subjects, etc.). This intermediary layer allows rapid retrieval of communication items without scanning the entire corpus, thereby increasing review speed while reducing IT resource consumption during both indexing and search phases.
Solution Approach 2:
The system performs preliminary indexing of communication items during or after data collection, organizing metadata and creating retrieval paths before the actual review process begins. This advance preparation enables fast searching during litigation review without consuming excessive resources during the critical review phase.
2Reliability
If all communication items are retained for potential litigation, then complete data is available for discovery, but the complexity of managing and reviewing the data increases
Solution Approach 1:
The patent segments the large corpus of communication items into manageable units indexed by multiple metadata dimensions (people, dates, subjects, communication types). This segmentation allows the system to handle complete data sets while reducing management complexity through structured organization and targeted retrieval capabilities.
Solution Approach 2:
The indexing system serves multiple functions simultaneously: it organizes data for storage efficiency, enables rapid searching by various criteria, supports relationship analysis between communication items, and facilitates selective production for discovery. This multi-functionality reduces overall system complexity despite handling complete data sets.
3Loss of time
If linear search methods are used to review communication items, then the search process is simple to implement, but the time required to identify relevant items increases
Solution Approach 1:
The patent employs an intermediary indexing structure that maps communication items to multiple metadata dimensions. This intermediary allows simultaneous searching by various criteria (person, date, subject, etc.) without linear scanning, dramatically reducing identification time while maintaining manageable system complexity through structured indexing.
Solution Approach 2:
The system adds multiple dimensional indices (people, dates, subjects, communication types) to the basic communication item data. This dimensional expansion enables multi-criteria searching and relationship analysis, reducing time to identify relevant items while organizing complexity into structured, manageable dimensions.
Data Source
AI summary
A mechanism to collate, interpret, target or view communication items retained by an organization is presented. Such a mechanism can be used as an aid in identifying communication items (e.g., documents) during electronic discovery, as well as discovery of communication chains. Embodiments of the present invention provide a method, system, apparatus and computer program product for storing communication data, generating a people map data structure using the communication data, generating an evidence map data structure using the communication data, and coupling the people map data structure and evidence map data structure.