Automated Naming Structures from File and Project Metadata
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Solution Overview
Problem
Existing software applications for managing construction project data files face challenges in ensuring accurate and efficient assignment of naming structures due to user-driven, file-based and folder-based approaches, which are labor-intensive, time-consuming, and prone to errors, leading to potential compliance issues and misunderstandings among teams.
Innovation Solution
A data-driven approach using metadata to automatically determine and generate naming structures for data files based on metadata analysis, reducing user intervention and minimizing errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If user-driven, file-based approach is used to assign naming structures, then flexibility in naming assignment is maintained, but time consumption and labor intensity increase significantly
Solution Approach 1:
The system pre-assigns naming structures to data files by analyzing metadata during file upload or storage, before users need to access or manage the files. This preliminary automated assignment eliminates the need for manual naming decisions later, reducing time consumption while maintaining flexibility through metadata-based classification.
Solution Approach 2:
The system enables data files to automatically determine their own naming structures by analyzing their inherent metadata properties (such as file type, project ID, discipline, etc.). Each file essentially names itself based on its own characteristics, eliminating the need for external user intervention while preserving the appropriateness of the naming structure.
2Adaptability or versatility
If manual naming assignment is used by users, then adaptability to specific file contexts is maintained, but error rates increase due to human oversight
Solution Approach 1:
The system replaces the manual mechanical process of user-based naming assignment with an automated computational system that analyzes file metadata and applies naming rules consistently. This substitution eliminates human errors while maintaining adaptability through programmable logic that can handle various file contexts and naming conventions.
Solution Approach 2:
The system continuously analyzes file metadata and provides feedback to automatically adjust and refine naming structure assignments. By monitoring file properties and comparing them against naming rules, the system ensures accurate and context-appropriate naming while maintaining high reliability through consistent application of predefined criteria.
3Productivity
If automated metadata-based naming is implemented, then productivity and accuracy improve, but system complexity increases
Solution Approach 1:
The system uses a universal metadata analysis framework that can handle multiple file types, naming conventions, and project requirements through a single automated process. By creating a multi-functional naming system that adapts to different contexts through metadata interpretation, the solution improves productivity without proportionally increasing complexity, as the same core mechanism serves multiple purposes.
Data Source
AI summary
A computing platform is configured to: (i) receive, from a first client station, a data file; (ii) obtain metadata associated with the data file; (iii) determine, based on at least a first set of metadata from the obtained metadata associated with the data file, a naming structure to use for the data file; (iv) generate, based on the determined naming structure and at least a second set of metadata from the obtained metadata, a proposed name for the data file; and (v) transmit, to a second client station, a communication identifying the proposed name and thereby cause an indication of the proposed name for the data file to be presented at a user interface of the second client station.