Dynamic Composite Data Dictionary for Interoperable Dataset Management
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Solution Overview
Problem
Conventional data storage and computing technologies face challenges in managing and analyzing large, complex datasets due to compatibility issues between different formats and systems, leading to inefficiencies in data interoperability, manual intervention, and user frustration in data procurement and analysis processes.
Innovation Solution
A collaborative dataset consolidation system that includes a data project controller and dataset ingestion controller to transform and consolidate datasets into a unified format, enabling interoperability and facilitating data project formation, analysis, and visualization through a unified workspace interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If conventional data storage and computing technologies are used to manage large, complex datasets, then data capacity and storage capability are improved, but data interoperability and compatibility between different formats and systems deteriorate
Solution Approach 1:
The patent implements a universal data dictionary that serves multiple functions: it defines data structures, establishes relationships between datasets, enables cross-system interoperability, and provides a common framework for diverse data formats. This single structure performs what would otherwise require multiple separate systems, resolving the contradiction between handling large data quantities and maintaining interoperability.
Solution Approach 2:
The data dictionary acts as an intermediary layer between disparate data sources and analysis tools. It mediates compatibility issues by providing standardized definitions and relationships that allow different systems to communicate effectively, thus maintaining interoperability while supporting large, complex datasets.
2Adaptability or versatility
If multiple different data formats and systems are used, then data versatility and coverage are improved, but manual intervention and operational complexity increase
Solution Approach 1:
The system enables automated data discovery and relationship establishment through the data dictionary. Tools can automatically query the data dictionary to understand data structures and relationships without manual configuration, allowing the system to serve itself in terms of interoperability and reducing the need for manual intervention despite supporting diverse data formats.
3Ease of operation
If conventional data accessing techniques are used, then simplicity of access is improved, but effectiveness in analyzing complex, large-scale datasets deteriorates
Solution Approach 1:
The data dictionary performs preliminary organization and definition of data structures, relationships, and metadata before actual data analysis occurs. This pre-structuring work enables simpler access techniques to remain effective by ensuring data is already organized and described in a usable format, eliminating the need for complex access procedures while maintaining analysis effectiveness.
Data Source
AI summary
Various embodiments relate generally to data science and data analysis, computer software and systems, network communications to interface among repositories of disparate datasets and computing machine-based entities that seek access to the datasets, and, more specifically, to a computing and data storage platform configured to provide one or more computerized tools that facilitate data projects by providing an interactive, project-centric workspace interface that may include, for example, a unified view in which to identify data sources, generate transformative datasets, and/form queries over a composite data dictionary coupled to collaborative computing devices and user accounts. For example, a method may include forming a first data dictionary, linking a dataset associated with the first data dictionary to another dataset, which may be associated with a second data dictionary, and forming a dynamic composite data dictionary.