Double Entry Validation Tool

Background

About

This tool takes in a *.tsv or *.csv export from Qualtrics, and compares rows of data based on a unique participant ID column, a column identifier to begin comparisons at, and a "double entry" participant ID prefix. Through the GUI, users can efficiently analyze data reports from Qualtrics to identify discrepancies between the first entry of row of data, and the "double entry". This is useful for identifying and reconciling user input data.

What is a "double entry"?

Double-entry bookkeeping, also known as double-entry accounting, is a method of bookkeeping that relies on a two-sided accounting entry to maintain financial information. Every entry to an account requires a corresponding and opposite entry to a different account. The double-entry system has two equal and corresponding sides known as debit and credit. A transaction in double-entry bookkeeping always affects at least two accounts, always includes at least one debit and one credit, and always has total debits and total credits that are equal. The purpose of double-entry bookkeeping is to allow the detection of financial errors and fraud. - Wikipedia (2023-02-19)

In the context of this tool, a double-entry is a re-entry of an existing record in a system like Qualtrics (or simply, an additional row of data in a *.tsv or *.csv file) that should be compared to an existing row.

This tool facilitates this comparison process by reading in a supported file and several parameters specified by the user to automatically identify mismatches in the two entries in a manner consistent with the requirements of the Family and Culture Lab at UC Berkeley.

Features

• Takes in a *.tsv or *.csv Qualtrics export file, compares double-entry rows, and identifies mismatched data.
• Exports mismatched data to a file compatible with Qualtrics for import.
• Basic user interface is provided for broad usability.

Execution

1. Download the latest release *.jar file from GitHub if you have not already done so. Alternatively, you may opt to follow the instructions under "Build" to create the *.jar file yourself.
2. Download the JDK from Oracle if you have not already done so.
3. Go to the directory where your *.jar file is located. You may opt to follow this tutorial if you have not done this before.
4. Start the program by typing java -jar YOUR_JAR_NAME.jar, replacing YOUR_JAR_NAME with the name of the file you downloaded or built manually.

Demo

Sample data is included in this distribution, it can also be found in the SampleData folder on GitHub. The ID column is AF, the first-relevant column is C, and the prefix for double-entry data is X_.

Development

Build

./gradlew build
./gradlew shadowJar

Future Improvements

• Integration tests and unit tests, this was rushed to fulfill an immediate need within the lab.
• Refactoring of code into more classes, the responsibility of classes are somewhat meshed and can be improved.

Additional Notes

Originally developed in April 2020. Refactored in February 2023. Created for the Family and Culture Lab at Berkeley, CA as a side-project.