Project Data Transfer Containers for Automated Metadata Handling
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Solution Overview
Problem
The manual processes involved in transferring project data, such as CAD models and data sheets, from a manufacturer to a customer are complex and time-consuming, affecting further data processing efficiency.
Innovation Solution
A method is introduced that involves creating separate containers for data units and unit-related metadata, along with a main container for project-related metadata, forming a transfer-compatible data structure that is output to a receiver system, enabling automated and secure data transfer.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual processes are used to transfer project data from manufacturer to customer, then data can be transferred with basic structure, but the process becomes complex and time-consuming
Solution Approach 1:
The patent segments project data into distinct data units (documents, drawings, images) and associates metadata with each unit. This segmentation enables automated processing by structure the data in a way that can be systematically extracted, transferred, and imported without manual intervention, directly addressing the productivity-time contradiction.
Solution Approach 2:
The patent implements preliminary action by pre-structuring data in a standardized format with embedded metadata before transfer. The data units are prepared with associated metadata (data context, classification, version information) in advance, enabling the receiver system to automatically import and process the data without time-consuming manual compilation and metadata creation.
2Reliability
If manual metadata assignment is performed for each data unit, then data context information can be captured, but the process becomes complex and error-prone
Solution Approach 1:
The patent merges data units with their associated metadata into a unified structured format. Each data unit is combined with its metadata (data context, classification, version information) as an integrated package. This merging ensures that data context accuracy is maintained while reducing process complexity, as the combined structure can be automatically processed without separate manual metadata assignment steps.
Solution Approach 2:
The patent uses copying by creating standardized templates for data units with predefined metadata structures. Once a data unit is structured with its metadata in the standardized format, this structure can be copied and reused for similar data units, ensuring consistency and accuracy of data context information while significantly reducing the complexity and time required for metadata assignment.
3Productivity
If data is manually searched and compiled from project database, then complete project data can be gathered, but the process is time-consuming and affects further processing
Solution Approach 1:
The patent implements feedback mechanisms where the standardized data structure includes metadata that provides information about the completeness and status of data units. The metadata contains version information, data context, and classification that enable automatic verification of data completeness. This feedback system ensures all necessary project data is gathered while accelerating the compilation process through automated validation.
Solution Approach 2:
The patent applies parameter changes by transforming unstructured or semi-structured project data into a standardized format with defined parameters and metadata fields. This parameterization enables automated searching, filtering, and compilation of complete project data sets, dramatically increasing compilation speed while maintaining data completeness through systematic parameter-based validation.
Data Source
AI summary
A method for supporting a data transfer of project data includes providing a plurality of data units and acquiring unit-related meta data. The method also includes creating a plurality of individual containers. One of the data units and the assigned metadata are stored separately from each other in each individual container. The method also includes acquiring project-related metadata for information about a data context of the individual containers. The method also includes creating a main container in which the individual containers and the project-related metadata are stored separately from each other. The method also includes outputting the main container via the transmitter system for the receiver system.