Mark Duration Visualization for Long Record Data Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Users of test and measurement instruments face challenges in analyzing long record length data due to the impracticality of manually examining digitized signals for interesting events, as zooming in for detail takes too long and zooming out reduces detail, and existing methods do not utilize mark duration for further analysis.
Innovation Solution
Generating marks with a start location, duration, focus, and optional information for each interesting event in long record length data, allowing for visualization of mark duration and enabling automated measurements, filtering, and complex analysis such as generating histograms and trend plots.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the user zooms in on the data to see interesting events in sufficient detail, then the level of detail is improved, but the time required to pan the zoom window across the long record length data becomes unacceptable
Solution Approach 1:
The system performs preliminary analysis by automatically scanning the entire long record length data to identify interesting events and place marks at their locations before the user needs to examine them. This preliminary action eliminates the need for manual panning through the data, as users can directly navigate to pre-identified interesting events marked with indicators.
Solution Approach 2:
Marks serve as intermediaries between the user and the detailed data. Instead of manually panning through raw data to find interesting events, users interact with mark indicators that represent pre-identified events. The marks mediate the analysis process by capturing and presenting key information without requiring direct manual examination of the entire data set.
2Loss of time
If the user zooms out the zoom window to perform panning in an acceptable amount of time, then the time required is reduced, but the level of detail is so reduced that the user may not see the interesting events
Solution Approach 1:
The data analysis is segmented into two distinct phases: an automated scanning phase that identifies interesting events across the entire long record length data, and a user examination phase where users view detailed information at pre-identified mark locations. This segmentation allows the system to maintain both efficiency (through automated scanning) and detail (through focused user examination at marked positions).
Solution Approach 2:
The system creates copies of interesting events in the form of marks that contain condensed information about the original data features. These mark copies allow users to examine event details without needing to view the entire original data set at high zoom levels, thus maintaining detail while reducing the time required for analysis.
3Productivity
If marks are created to identify interesting events, then navigation efficiency is improved, but the duration of marks is not utilized for further analysis or visualization
Solution Approach 1:
Marks are designed with multi-functionality to serve both navigation purposes and analysis purposes. Each mark contains not only position information for navigation but also duration information and associated source data that can be used for various types of analysis including measurements, filtering, histogram generation, and trend analysis. This universal design allows the same mark structure to support multiple analytical functions.
Solution Approach 2:
The mark structure is extended from a simple position indicator to a multi-dimensional data structure that includes position, duration, focus, and optional information fields. This dimensional expansion allows marks to encode additional information about the interesting events, enabling sophisticated analysis operations such as measuring event durations, comparing event characteristics, and generating statistical analyses without requiring separate data structures.
Data Source
AI summary
A method of analysis of long record length data using mark duration includes displaying together with a portion of the long record length data each mark that identifies a specified feature of interest together with the mark duration. Associated with the mark may be text identifying the feature of interest, measurement values associated with the duration of the mark, or a combination thereof. Multiple sets of marks may be generated for the long record length data, which sets may be combined to generate new marks with duration. The marks also may be filtered to further refine the marks to be displayed according to user specified criteria. In this way analysis of long record length data representing an acquired signal may be readily automated so a user may move from one interesting event to another without having to pan through the long record length data.