Interpolated Data Object Embedding via Dynamic Links
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Solution Overview
Problem
Conventional modeling platforms struggle with generating interpolated data objects that can be dynamically accessed and manipulated by multiple applications, as they often require manual estimation and lack mechanisms for dynamic data linking, leading to inefficiencies in producing target outputs from unknown inputs.
Innovation Solution
The development of systems and methods that embed interpolated data objects into application data files via dynamic data links, allowing for dynamic manipulation and sharing across applications, enabling the interpolation engine to generate and update input values to produce target outputs efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional modeling platforms are used to generate interpolated data, then the modeling engine can produce precise outputs from known inputs, but the interpolated data objects cannot be dynamically accessed or manipulated by other applications
Solution Approach 1:
The patent introduces an intermediary component that acts as a bridge between the modeling engine and other applications. This intermediary enables dynamic data links that allow interpolated data objects to be accessed and manipulated by external applications while maintaining the integrity of the original modeling engine. The intermediary translates and facilitates data exchange between different application interfaces.
Solution Approach 2:
The patent implements a universal data interface that allows the interpolated data objects to serve multiple functions across different applications. The data linking mechanism is designed to be application-agnostic, enabling any application to access, read, write, and manipulate interpolated data objects without requiring application-specific customization of the core modeling engine.
2Productivity
If manual estimation and back-calculation are used to derive input sets, then the process can produce target outputs, but the process is time-consuming and requires iterative adjustments
Solution Approach 1:
The patent implements preliminary action by pre-calculating and storing the relationships between inputs and outputs in the modeling engine. When target outputs are provided, the engine can rapidly derive input sets by referencing pre-established mathematical models and relationships, eliminating the need for time-consuming manual iterative adjustments and back-calculation trials.
Solution Approach 2:
The patent incorporates feedback mechanisms that automatically adjust input values based on the difference between actual and target outputs. The system continuously monitors output results and uses feedback loops to refine input estimates, automating the iterative adjustment process that previously required manual intervention and significantly reducing the time required to converge on accurate input sets.
3Adaptability or versatility
If interpolated data objects are generated but not embedded in application data files, then the data remains isolated, but embedding requires dynamic data link mechanisms
Solution Approach 1:
The patent uses an intermediary embedding mechanism that facilitates the integration of interpolated data objects into application data files. This intermediary layer handles the complexity of dynamic data linking, allowing data to be shared across applications without requiring each application to implement its own complex embedding logic. The intermediary manages data formats, links, and update protocols.
Solution Approach 2:
The patent implements a copying mechanism that creates reference copies of interpolated data objects within application data files. Rather than duplicating the entire data structure, the system creates lightweight references that point to the original interpolated data objects, enabling multiple applications to access and manipulate the same data objects efficiently while maintaining data integrity and reducing storage overhead.
Data Source
AI summary
Embodiments relate to systems and methods for embedding an interpolated data object in an application data file. A database management system can store operational data, such as financial, climate or other information. A user can input or access target data, representing an output desired to be generated from an interpolated set of input data. Thus, the average air temperature of a region may be known for several years, along with other inputs including water temperature, wind speed, and other data. The target data can include an expected average temperature for the current year. The interpolation engine can receive the current-year target temperature, and generate water temperatures, wind speeds, and other variables that produce the target temperature. In aspects, the interpolation engine can embed the interpolated data as an object in a local or remote spreadsheet or other local data file via dynamic data links, to permit automatic updating of the embedded interpolated data.