Spreadsheet Semantic Enrichment via Interpretation Layer
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Solution Overview
Problem
Spreadsheets lack the ability to be queried like databases, making it impossible to detect and solve security, data quality, compliance, and productivity issues related to data stored in them, as they cannot be interpreted effectively.
Innovation Solution
A method that automatically interprets the contents of spreadsheets in normal business terms, converting data into semantically enriched schemas, and allows for querying, linking, reformatting, and maintaining spreadsheets, while addressing issues like misspelled words and ambiguous meanings by leveraging grammar terms and prior knowledge.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If spreadsheets are used to store and manage data, then data storage flexibility and ease of use are improved, but the ability to query and interpret data like databases is lost
Solution Approach 1:
The patent introduces an interpretation layer that acts as an intermediary between the spreadsheet interface and the data. This layer automatically interprets cell contents, formulas, and visual formatting to extract semantic meaning, enabling database-like querying capabilities while preserving the spreadsheet's ease of use. The interpretation layer translates spreadsheet elements into structured data representations without requiring users to change their interaction with the spreadsheet interface.
2Device complexity
If spreadsheets store data in atomic tuples format, then data storage simplicity is improved, but data interpretation and semantic understanding become difficult
Solution Approach 1:
The patent applies preliminary interpretation actions to spreadsheet data during the import or loading phase. The system pre-processes cell contents, formulas, and visual elements to extract and attach semantic metadata to the atomic tuples. This preliminary action enriches the simple storage format with interpretive information, enabling semantic understanding without changing the fundamental simplicity of the storage structure.
Solution Approach 2:
The patent transforms the interpretation parameters of spreadsheet data by analyzing multiple attributes including cell content, formula logic, visual formatting, and contextual relationships. By changing how parameters are interpreted and combined, the system extracts semantic meaning from atomic tuples while maintaining storage simplicity. The interpretation process dynamically adjusts parameters based on data patterns and contextual clues.
3Productivity
If automatic interpretation of spreadsheet contents is implemented, then data querying and analysis capabilities are improved, but processing time and computational resources increase
Solution Approach 1:
The patent implements partial interpretation by selectively analyzing only the portions of spreadsheet data that are relevant to current queries or operations. Rather than fully interpreting all cells and formulas in a spreadsheet, the system performs interpretation on-demand for specific ranges or elements, reducing processing time while maintaining analytical capability. This partial action approach balances thoroughness with efficiency.
Data Source
AI summary
Embodiments of the invention convert data from atomic tuples found in data sources such as spreadsheets (e.g., raw numbers, words, and formatted dates) into semantically enriched schemas and associated tuples. In addition to the data content, visual content, such as font and background color, is also analyzed as a part of the interpretation process. Embodiments of the invention also provide methods of interacting with the raw data via the semantically enriched schema tuples.