Contributor Data Transformation in Document Flow Systems
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing data processing systems face challenges in efficiently extracting and processing contributor information from complex document flows, as this data is often spread across multiple documents and requires time-consuming extraction and transformation to match user access privileges and needs.
Innovation Solution
A method for processing data in an application platform that involves receiving requests for contributor information, retrieving associated documents, transforming the data based on user access privileges, and communicating the tailored data back to the user, utilizing a transformation module to customize the view according to the user's role and permissions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If data for contributors is extracted from multiple documents in a document flow, then completeness of contributor information is improved, but processing time increases
Solution Approach 1:
The system pre-identifies and extracts contributor data from multiple documents in the document flow before the user requests it. By performing the extraction action in advance, the system reduces the time required when the actual query is made, while still gathering complete contributor information from all relevant documents.
Solution Approach 2:
The patent extracts contributor information from the complex document flow structure by identifying and separating contributor-related data from multiple documents. This extraction process isolates the relevant contributor data (such as creator, approver, reviewer roles) from the broader document context, enabling efficient retrieval without processing entire documents.
2Adaptability or versatility
If contributor data is transformed to match user access privileges, then data security and relevance are improved, but transformation complexity increases
Solution Approach 1:
The system applies different transformation rules to different portions of contributor data based on user access privileges. Instead of uniformly transforming all data, it selectively customizes the view of contributor information according to the specific user's role and permissions, making the transformation process more efficient and targeted.
Solution Approach 2:
The transformation of contributor data is made dynamic and adaptive to the user's access privileges and current context. The system adjusts the data presentation in real-time based on user characteristics, allowing the same contributor data to be transformed differently for different users without requiring complex static transformation rules for each user type.
3Loss of information
If all contributor data from document flow is retrieved, then data completeness is improved, but data accessibility for specific users deteriorates
Solution Approach 1:
The system extracts only the relevant contributor data needed for the user's current context from the complete document flow. By taking out and presenting only the necessary contributor information (filtered by user privileges and current application context), the system maintains data completeness in the backend while improving accessibility by presenting a tailored, manageable view to the user.
Data Source
AI summary
Systems and methods are disclosed for processing data in an application platform. The method may include receiving at runtime a request for data about contributors to at least one document. Data may be determined for a set of contributors to the at least one document. The data for the set of contributors may be transformed based on at least one transformation rule. The transformed data for the set of contributors may be communicated in response to the request. The request may include context data indicating one or more of a user of a computing device, a user session of the computing device, a currently active application on the computing device, and an active screen of the computing device. The determining the data may include identifying, using at least some of the context data, a document associated with the currently active application.