Centralized Data Transformation for Survey Tools
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Solution Overview
Problem
Current remediation systems face challenges in efficiently transforming diverse survey data formats from multiple host-entities into a unified format, leading to increased computational load and complexity for survey tools, particularly on resource-constrained devices like mobile devices, which hinders the goal of minimizing the burden on these devices.
Innovation Solution
A centralized data transformation architecture is implemented, where survey data from host-entities is transmitted to a server for processing, using service-keys to identify data sources and format interpretation services to convert data into desired formats, thereby shifting the transformation burden from the host-entities to the server.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If data transformation is performed locally on host-entities using survey tools, then data format conversion can be achieved, but computational load and complexity increase on resource-constrained devices
Solution Approach 1:
The patent extracts the data transformation function from the host-entity survey tools and relocates it to a centralized server. The survey tools on host-entities only collect and transmit raw data in their native formats, while the server performs all format conversion and normalization operations. This extraction eliminates the computational burden from resource-constrained devices while maintaining transformation capabilities.
Solution Approach 2:
The patent introduces a centralized server as an intermediary between survey tools and the remediation system. This intermediary receives diverse survey data in various formats, performs the necessary transformations, and delivers standardized data to the remediation system. The intermediary handles all complexity of format conversion, allowing simple survey tools to work with multiple data formats without increasing their computational requirements.
2Adaptability or versatility
If multiple survey tools gather data in different formats from host-entities, then comprehensive survey coverage is achieved, but data format diversity increases transformation complexity
Solution Approach 1:
The patent merges all data transformation operations into a single centralized location (the server). Instead of each survey tool independently handling format conversion, all transformation functions are combined and executed by the server. This consolidation maintains the ability to handle diverse data formats from multiple survey tools while eliminating redundant transformation logic and reducing overall system complexity.
Solution Approach 2:
The centralized server is designed with universal data transformation capabilities that can handle multiple survey data formats simultaneously. The server implements a unified transformation framework that adapts to various input formats from different survey tools and converts them all to a standardized format, providing multi-functional transformation support without requiring separate processing logic for each format.
3Productivity
If survey tools on host-entities perform format conversion, then data can be transmitted in desired formats, but the burden on resource-constrained devices increases
Solution Approach 1:
The patent extracts the energy-consuming data transformation operations from the host-entity survey tools and relocates them to the server. Survey tools on resource-constrained devices only perform lightweight data collection and transmission in their native formats, while the server handles all format conversion. This extraction dramatically reduces energy consumption on host-entities while maintaining efficient data transmission.
Solution Approach 2:
Instead of having survey tools convert data to desired formats before transmission (the conventional approach), the patent inverts the process: survey tools transmit data in their original formats, and the server performs conversion after reception. This inversion eliminates the need for format conversion on resource-constrained devices, reducing their energy burden while achieving the same data transmission efficiency through server-side processing.
Data Source
AI summary
A method of facilitating transformation of survey data from being in at least one foreign format used by a survey-tool to being in a desired format may include: receiving instances of foreign data from survey-tools, the foreign data being in foreign format used by the survey-tools, respectively; and appending, to the instances of foreign data, service-keys to identify the service tools which gathered the foreign data, respectively, to produce a data block that includes key-and-foreign-data pairs. Another such method may include: receiving such a data block; culling from the block key-and-foreign-data pairs; and operating upon the pairs to transform respective chunks of foreign data from being in respective foreign formats into being in corresponding desired formats according to corresponding service-keys, respectively.