Semantic Syntactic Metadata Linking for Heterogeneous Data
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Solution Overview
Problem
Current data management systems face challenges in accessing and organizing highly dimensional, heterogeneous data due to the lack of standards for describing semantic and syntactic properties, which hinders collaboration across institutional boundaries and is exacerbated by rapid data generation.
Innovation Solution
A method for managing semantic and syntactic metadata involves receiving heterogeneous data, capturing and linking semantic and syntactic metadata, and storing it in a repository, using a system that determines data source, captures metadata attributes, and generates parsers for standardized syntax, enabling efficient data organization and access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional data management systems are used to store heterogeneous data, then data storage is simple, but data accessibility and organization efficiency deteriorate due to lack of semantic and syntactic standards
Solution Approach 1:
The patent segments data into multiple hierarchical levels including raw data, annotated data with syntactic metadata, and structured data with semantic metadata. This segmentation allows different levels of data processing and access, improving accessibility without requiring the entire system to handle all complexity simultaneously.
Solution Approach 2:
The patent introduces metadata as an intermediary layer between raw heterogeneous data and data access operations. Syntactic metadata describes data structure and format, while semantic metadata describes data meaning and context. This intermediary layer enables standardized access without requiring direct handling of raw data complexity.
2Adaptability or versatility
If data standards for semantic and syntactic properties are implemented, then data organization and collaboration improve, but system complexity and implementation difficulty increase
Solution Approach 1:
The patent creates universal metadata schemas that can describe multiple types of heterogeneous data (images, audio, video, text) using the same syntactic and semantic frameworks. This universality enables collaboration across different data types and institutional boundaries without requiring separate standards for each data type.
Solution Approach 2:
The patent applies syntactic annotation and semantic tagging to data during the data ingestion and processing stages, before data access operations occur. This preliminary action ensures that metadata is already available when needed for collaboration, rather than requiring complex real-time analysis during data access.
3Loss of information
If comprehensive metadata capture is performed on all heterogeneous data, then data description accuracy improves, but processing time and computational resources increase
Solution Approach 1:
The patent implements a tiered metadata capture approach where syntactic metadata (basic structure and format) is captured for all data, while semantic metadata (detailed meaning and context) is captured selectively based on data type, importance, and available resources. This partial action approach ensures essential description accuracy without requiring exhaustive metadata for every data element.
Solution Approach 2:
The patent performs metadata capture during data ingestion and initial processing stages, rather than on-demand during data access. This preliminary action allows batch processing of metadata extraction, reducing the time impact on individual data access operations while maintaining comprehensive description accuracy.
4Productivity
If rapid data generation is accommodated without standardized metadata, then data ingestion speed is maintained, but data usability and access efficiency deteriorate
Solution Approach 1:
The patent implements automated syntactic annotation and semantic tagging that occurs during or immediately after data ingestion, rather than as a separate post-processing step. This preliminary action ensures that even rapidly ingested data carries standardized metadata, maintaining both ingestion speed and data usability.
Solution Approach 2:
The patent employs automated metadata extraction systems that can independently analyze and annotate data without requiring manual intervention. This self-service approach to metadata generation maintains data usability standards even as data ingestion rates increase, without proportionally increasing processing overhead.
Data Source
AI summary
A method and system for managing semantic and syntactic metadata. Heterogeneous data is received. After the heterogeneous data is received, the semantic metadata associated with the received heterogeneous data is captured and syntactic metadata associated with the received heterogeneous data is captured. The semantic metadata describes contextually relevant or domain-specific information about data based on an industry-specific or enterprise-specific metadata model or ontology. The syntactic metadata included grammatical rules and structural patterns governing an ordered use of formats and arrangement pertaining to specified data. The received heterogeneous data and said captured semantic metadata and said syntactic metadata are logically linked. The heterogeneous data is stored in a repository.