Automated Spreadsheet Metadata Generation via Table Detection
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Solution Overview
Problem
Defining metadata for large spreadsheets is tedious and prone to human error, making it inefficient for business assessment and reporting software applications.
Innovation Solution
Automatically detecting tables, determining table orientation, and creating metadata such as object label names, object qualifications, and object data types within spreadsheets and other data files, reducing the burden on end-users by processing data to facilitate data exploration and reporting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If metadata is manually defined for spreadsheet columns, then accuracy and correctness of metadata can be ensured, but the process becomes tedious and time-consuming
Solution Approach 1:
The system performs self-service by automatically detecting tables, determining table orientations, inferring column data types, and generating metadata without requiring manual user input. The software analyzes the spreadsheet structure itself to create metadata definitions, eliminating the tedious manual process while maintaining reasonable accuracy through automated detection algorithms.
Solution Approach 2:
The system performs preliminary actions by pre-defining metadata structures, table orientations, and data types before the user needs to use the data for analysis or reporting. By automatically preparing metadata in advance based on spreadsheet structure analysis, the system eliminates the need for users to manually define metadata at the time of data loading.
2Productivity
If all metadata is automatically generated, then user workload is reduced, but the risk of human error and incorrect metadata increases
Solution Approach 1:
The system incorporates feedback mechanisms where the automatically generated metadata can be reviewed, validated, and corrected by users if needed. The detection algorithms analyze spreadsheet patterns and provide confidence indicators, allowing users to verify automated metadata generation and make adjustments when necessary, thus maintaining reliability while improving productivity.
3Manufacturing precision
If manual metadata definition is required for large spreadsheets, then metadata quality can be maintained, but the complexity and difficulty of the process increases
Solution Approach 1:
The system segments the metadata generation process into distinct automated components: table detection, orientation determination, column data type inference, and metadata assembly. By breaking down the complex task of metadata definition into separate detectable and inferable elements, the system maintains metadata quality while reducing process complexity and user burden.
Data Source
AI summary
Apparatus, systems, and methods may operate to receive, sequentially, individual lines of information included in a file stored in an electronic storage medium; to locate one or more tables in a spreadsheet when at least two of the lines in a sequence are consecutive lines that begin with a non-empty cell and have a matching length; to determine a vertical orientation or a horizontal orientation of the tables based on an arrangement of the information within the lines and across the lines; and to create metadata from the information, based on the arrangement. The metadata may comprise object label names, object qualifications, and/or object data types. Additional apparatus, systems, and methods are disclosed.