Object-Centric Data Analysis With Reusable Filtering Workflows
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Solution Overview
Problem
Existing data analysis systems lack an effective object-oriented methodology for analyzing large data sets with numerous associated objects, leading to inefficiencies and a lack of systems that track and display the steps of down-selecting and filtering objects, and re-applying analysis to another set of objects.
Innovation Solution
A system and user interface that provides an object-centric methodology for analyzing data sets, allowing users to visualize, drill down, and search for linked objects, with tools for generating plots and tracking analysis steps, enabling efficient navigation and analysis of complex data sets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If time-series centric methodology is used for analyzing data sets with many associated objects, then data analysis can be performed, but the analysis becomes inefficient when objects need to be down-selected before reviewing data
Solution Approach 1:
The system segments the data analysis process into distinct phases: first selecting and visualizing objects of interest, then drilling down to examine specific time-series data. This separates the object selection function from the data visualization function, allowing efficient object-level filtering before data-level analysis.
Solution Approach 2:
The system inverts the conventional time-series centric approach by starting with object selection and visualization, then moving to time-series data examination. This inversion enables users to first identify relevant objects through the object browser, then efficiently access their time-series data without having to filter through all objects first.
2Adaptability or versatility
If ontology oriented methodology is used, then data analysis advantages are provided, but certain data sets with many associated objects and complicated object associations require down-selecting objects before analyzing data
Solution Approach 1:
The system implements a nested structure where the object browser can display objects at different levels of association complexity. Users can navigate through object associations in a hierarchical manner, drilling down from high-level object summaries to detailed time-series data, allowing efficient handling of complex object associations without overwhelming the user.
Solution Approach 2:
The system performs preliminary object selection and visualization before time-series data analysis. By allowing users to pre-select and visualize objects of interest in the object browser, the system prepares the data structure in advance, enabling faster subsequent time-series analysis without requiring full data loading or complex filtering operations.
3Productivity
If no system tracks and displays steps for down-selecting and filtering objects, then data analysis can proceed, but users cannot efficiently navigate and re-apply analysis to another selected set of objects
Solution Approach 1:
The system provides feedback by tracking and displaying the steps performed for down-selecting and filtering objects. The object browser maintains state information about selected objects and analysis steps, allowing users to review previous selections and re-apply analysis to different object sets. This feedback mechanism enables efficient navigation and reuse of analysis procedures.
Data Source
AI summary
Methods and systems for generating and analyzing visualizations based on a group of sets of data objects. One system includes processors executing instructions to present the sets of data objects in a selectable format on a display device, receive a user selection of a first set of data objects, generate a user interface comprising an indication of the first set of data objects and a plurality of selectable tools to generate a first data visualization of the first set of objects from one or more operations to the first set of objects, receive a user selection of a second set of data objects, receive a user selection to cause the application of the one or more operations to the second set of data objects, and update the user interface to comprise a second visualization based on the one or more operations performed on the second set of data objects.