Layered Dataset Linking for Cross-Platform Data Interoperability
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Solution Overview
Problem
Conventional data management and analysis techniques face challenges in efficiently linking and managing datasets across disparate platforms, leading to data silos, manual intervention requirements, and unreliability due to inconsistencies and anomalies, which hampers data interoperability and sharing.
Innovation Solution
A collaborative dataset consolidation system that converts datasets into atomized data points and generates layered data files, enabling interoperability and linking across platforms, with features like inference engines and layer data generators to enhance data accuracy and facilitate query accessibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If conventional data management techniques are used to store datasets on different platforms, then data storage capacity is maintained, but data interoperability and linking capability deteriorate, resulting in data silos
Solution Approach 1:
The patent implements a universal data model that enables datasets from different platforms to be represented and linked through common structures. The system uses standardized data representations that can accommodate multiple data types and sources, allowing data to be both stored and interoperable through a unified framework that works across diverse platforms
2Reliability
If manual intervention is used to link datasets across platforms, then data accuracy can be maintained, but productivity and automation level deteriorate
Solution Approach 1:
The system employs automated inference engines that self-service the data linking process by automatically inferring relationships between datasets based on their contents and metadata. The patent describes how the system can autonomously identify and establish connections between datasets without requiring manual intervention, while maintaining accuracy through systematic analysis methods
3Adaptability or versatility
If datasets are standardized for interoperability, then data sharing is improved, but device complexity and processing requirements increase
Solution Approach 1:
The patent implements a layered data model that segments data representation into distinct levels: raw data, standardized intermediate representations, and application-specific interpretations. This segmentation allows standardization to occur at the intermediate layer without requiring complete transformation of all data, thereby reducing the complexity burden while maintaining interoperability benefits
4Productivity
If automated data standardization is implemented, then productivity is improved, but reliability deteriorates due to inconsistencies and anomalies in automated processing
Solution Approach 1:
The system incorporates feedback mechanisms where the automated standardization process continuously monitors and adjusts its operations based on detected inconsistencies and anomalies. The patent describes how the system can identify processing errors, validate data transformations, and correct deviations from expected standards, thereby maintaining reliability while preserving automation benefits
Data Source
AI summary
Various embodiments relate generally to data science and data analysis, and computer software and systems to provide an interface between 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 that facilitates consolidation of one or more datasets, whereby data ingestion is performed to form data representing layered data files and data arrangements to facilitate, for example, interrelations among a system of networked collaborative datasets. In some examples, a method may include forming a first layer data file and a second layer data file, assigning addressable identifiers to uniquely identify units of data and data units to facilitate the linking of data, and implementing selectively one or more of a unit of data and a data unit as a function of a context of a data access request for a collaborative dataset.