Dynamic Data Naming for File Organization and Sharing
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Solution Overview
Problem
Existing data management systems lack the ability to generate data names based on intended use, leading to inefficiencies in file organization and sharing processes.
Innovation Solution
A data management device and method that utilizes a processor to generate and attach distinct data names to data based on specific rules for saving and sharing, allowing for unique naming conventions depending on the intended use, such as including sequence numbers and timestamps for saved data and omitting timestamps for shared data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a uniform data naming method is used for all data, then the device complexity is reduced and ease of operation is improved, but the adaptability to different intended uses deteriorates
Solution Approach 1:
The data naming method dynamically changes based on the intended use of the data. The system determines whether data is to be saved or shared, and automatically applies the appropriate naming rule (first rule for saved data with sequence numbers and timestamps, second rule for shared data with omitted timestamps), making the naming system adaptive rather than static.
Solution Approach 2:
The naming parameters are changed according to the intended use. For saved data, the name includes sequence number and timestamp parameters; for shared data, the timestamp parameter is omitted. This parameter change approach allows the same naming system to serve multiple purposes effectively.
2Adaptability or versatility
If distinct naming rules are applied for different data uses, then the adaptability to intended use is improved, but the device complexity increases
Solution Approach 1:
The naming system is segmented into two distinct rule sets: the first rule for saved data and the second rule for shared data. Each rule is independently defined and applied based on the intended use, allowing complex naming requirements to be broken down into manageable, rule-based segments rather than a single complex algorithm.
Solution Approach 2:
The system dynamically selects which naming rule to apply based on the intended use determination. This dynamic selection mechanism manages complexity by only activating the relevant rule set at any given time, rather than maintaining all complexity simultaneously.
3Reliability
If timestamps are included in all data names, then the reliability for tracking and organization is improved, but the productivity for sharing processes deteriorates due to longer names
Solution Approach 1:
The naming system applies different quality characteristics to different data categories. Saved data receives full naming information including timestamps for reliable tracking, while shared data uses a simplified naming format without timestamps to maintain conciseness. Each data type receives the appropriate level of detail for its specific use case.
Solution Approach 2:
The timestamp parameter is selectively included or excluded based on the intended use. For saved data, the timestamp parameter is included to ensure reliable tracking; for shared data, the timestamp parameter is omitted to maintain name conciseness and improve sharing productivity.
Data Source
AI summary
A data management device includes a memory configured to save data and a processor. The processor is configured to save acquired data into the memory when the save command is received. The processor is further configured to execute a process which processes the data acquired by the acquisition unit when the specific command is received. The process is different from saving the data into the memory. The processor is still further configured to generate a first data name in accordance with a first rule and attach the first data name to the acquired data. Moreover, the processor is configured to generate a second data name in accordance with a second rule different from the first rule and attach the second data name to the acquired data.