Enterprise Information Management System Hierarchical Data Objects
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Solution Overview
Problem
Enterprise information management offices, such as family offices, face inefficiencies and inaccuracies due to reliance on disparate and disconnected technologies like email, spreadsheets, and generic calendar applications, leading to excess overhead and inability to meet obligations effectively.
Innovation Solution
An enterprise information management system (EIM system) that includes a server computing device generating data objects representing organizational features, hierarchically associating these objects, and storing relationships and metadata in a database, allowing for versioning and permissions-based access to improve data management and retrieval.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If disparate and disconnected technologies (email, spreadsheets, calendars) are used to manage operations, then ease of operation is maintained with familiar tools, but productivity deteriorates due to work inefficiency and excess overhead
Solution Approach 1:
The patent merges multiple disparate technologies (email, spreadsheets, calendars) into a single integrated enterprise information management system. The system combines document management, data storage, version control, and access management in one unified platform, eliminating the need to switch between separate tools and reducing overhead while improving productivity.
Solution Approach 2:
The system provides universal functionality by serving as a multi-purpose platform that handles document storage, data management, version control, access management, and information retrieval. This single system replaces multiple specialized tools, allowing users to manage all enterprise information needs in one location.
2Device complexity
If disparate and disconnected technologies are used, then device complexity is reduced by avoiding a new system, but reliability deteriorates due to inability to meet obligations effectively
Solution Approach 1:
The system segments information management into distinct functional modules: data objects for content storage, metadata for information description, version control for history tracking, and access management for security. This segmentation allows each component to be optimized independently while working together to provide reliable enterprise information management.
Solution Approach 2:
The system implements feedback mechanisms through version control and metadata tracking, allowing users to retrieve specific versions of data objects and understand the history of changes. This feedback capability ensures reliability by enabling audit trails, version recovery, and accurate information retrieval based on temporal and access requirements.
3Reliability
If a centralized system with version control is implemented, then reliability is improved through accurate data management, but device complexity increases due to hierarchical data structures and metadata management
Solution Approach 1:
The system uses a nested hierarchical structure where data objects contain metadata, which in turn reference relationships between objects. Version information is nested within data objects, and access management policies are nested at multiple levels. This nesting approach organizes complexity into manageable layers while maintaining reliable data management capabilities.
Solution Approach 2:
Metadata acts as an intermediary between data objects and user requests. The metadata layer abstracts the complexity of version control and relationships from users, providing simplified access through standardized queries. This intermediary structure manages the complexity of hierarchical data while maintaining interface simplicity.
4Measurement precision
If version control and metadata storage are implemented, then measurement precision is improved for data retrieval accuracy, but loss of information increases due to additional data storage requirements
Solution Approach 1:
The system extracts essential information about versions and relationships into separate metadata structures. Rather than storing complete copies of all version history within data objects, the system stores references and descriptions in metadata, reducing redundant information storage while maintaining precise retrieval capabilities through metadata queries.
Data Source
AI summary
A method for enterprise information management includes receiving first input information, from a first user, that corresponds to a first identifying a first feature of an organization. The method further includes generating, using the first input information, a first data object that represents the first feature of the organization. The method further includes generating a second data object based on second input information. The method further includes hierarchically associating the second data object with the first data object using the first input information and the second input information. The method further includes generating output information, in response to a second user accessing the first data object, based on the first data object, the second data object, and contact information associated with the second user. The method further includes displaying the output information on a display.