Industrial Asset Data Query Mapping Across Disparate Sources
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Solution Overview
Problem
Industrial asset data from disparate sources, stored in various data models, are difficult to query due to proprietary formats and lack of interoperability, locking data in silos and preventing effective use.
Innovation Solution
A computer-implemented method that maps queries to types of data objects across multiple data sources using a graph representing the industrial asset and semantic associations, allowing abstraction from specific data sources and formats, enabling retrieval of data objects without requiring knowledge of internal representations or connections between sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data objects are stored in proprietary data models from multiple vendors, then each software package can maintain its own data structure and semantics, but the data becomes locked in silos and cannot be queried across sources without familiarity with each proprietary format
Solution Approach 1:
The patent introduces an intermediary translation layer that converts proprietary data models from multiple vendors into a unified data model. This mediator component receives data objects from disparate sources, translates them into a common format with standardized schemas and semantics, and enables seamless querying without requiring users to understand the original proprietary formats. The intermediary resolves the contradiction by maintaining adaptability to multiple vendors while simplifying operations for end users.
Solution Approach 2:
The system segments the data integration process into distinct translation modules, each handling a specific proprietary data model. By dividing the complex integration task into manageable segments, the system can maintain compatibility with multiple vendors independently while presenting a unified interface. Each segment translates one vendor's proprietary format to the unified model, making the overall system adaptable yet easy to operate.
2Productivity
If specialized software packages with proprietary data models are used for different lifecycle phases, then each phase can be optimized with domain-specific tools, but the data objects cannot be retrieved across phases without deep knowledge of each data model
Solution Approach 1:
The patent implements a universal data model that can represent data objects from all lifecycle phases (design, commissioning, operation, maintenance) in a unified format. This multi-functional data model serves all phases simultaneously, allowing specialized tools to be used for each phase while ensuring data remains accessible across phases. The universal model preserves domain-specific semantics while enabling cross-phase queries without loss of information.
3Stability of the object's composition
If data sources are disconnected and use different data models, then each source can maintain its own structure and evolution, but the system cannot adapt to software evolution without breaking interoperability
Solution Approach 1:
The translation layer acts as a stable intermediary that absorbs the impact of software evolution. When a data source evolves its proprietary format, only the corresponding translation module needs to be updated, while the unified data model and other translation modules remain stable. This maintains data source independence while enabling adaptability to evolution without breaking interoperability across the system.
Data Source
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AI summary
A computer-implemented method (100) for retrieving data that relates to at least one industrial asset, comprising the steps of: • receiving (110), from a requesting entity (1), a query (2) for data objects (5a-5c) from one or more lifecycle phases of the at least one industrial asset; • mapping (120) the query (2) to one or more types (3a-3c) of data objects (5a-5c) that are available from one or more given data sources (4a-4c) relating to the at least one industrial asset; • obtaining (130), from the one or more data sources (4a-4c), one or more data objects (5a-5c) of the one or more types (3a-3c); • producing (140), from the one or more data objects (5a-5c), a response (6) to the query (2); and • transmitting (150) the response (6) to the requesting entity (1).