DataQ Culture - Data Quality Assessment Tool for Cultural Collections

The DataQ Culture is a data quality assessment tool designed for cultural collections, developed as a master's project at the Federal University of Espírito Santo (Ufes) in Brazil. The objective of DataQ Culture is to assist professionals and institutions in ensuring the integrity and accuracy of data within their cultural collections.

The tool is based on the Catalogue of Cultural Objects (CCO), an international reference guide for cataloging cultural objects. This enables users to calculate a quality index that reflects the level of confidence in the integrity and accuracy of data within a cultural collection. This index is established based on a set of criteria according to the guidelines outlined by CCO.

DataQ Culture provides an easy and efficient solution for maintaining data quality in cultural collections, enabling the identification of issues and correction of errors before they escalate or lead to irreparable damage. Additionally, the tool can also be used to monitor real-time data quality and ensure that data within a cultural collection remains accurate and up-to-date, following the international standards set by CCO.

How to Use

To utilize DataQ Culture, follow the instructions below:

For detailed installation steps, watch this video or perform the steps outlined:

1. Download DataQ Culture from the repository: https://github.com/AbeilCoelho/DataQ-Culture

2. Install the required prerequisites (requirements.txt)
   2.1 For Windows, use the command "python -m pip install -r requirements.txt"
   2.2 For Linux, use the command "python3 -m pip install -r requirements.txt"

3. Execute the app.py file.

4. An IP address will appear in the terminal. Access this IP address in your browser.
   4.1 It will be something like "http://127.0.0.1:5000/"

5. Upload a CSV file.

6. Align the columns of your file with those of CCO. For more details on this step, refer to this article.

7. Review the results and areas requiring attention to enhance the quality of your collection.

Contribution

If you wish to contribute to the development of DataQ Culture, feel free to submit pull requests or get in touch with the developers.

Authors

DataQ Culture was developed as a master's project at the Federal University of Espírito Santo (Ufes) in Brazil by the following authors:

• Abeil Coelho Júnior (UFES)

Supervised by:

• Daniela Lucas da Silva Lemos (UFES)
• Fabrício Martins Mendonça (UFJF)

License

This project is licensed under the MIT License - refer to the LICENSE.md file for details.