CSV-2-RDF-Converter

This Python script converts data stored in a CSV (Comma-Separated Values) file into RDF (Resource Description Framework) triples serialized in the .nt format. It's a handy tool for transforming tabular data into a format suitable for use in semantic web applications, linked data, and knowledge graphs.

Features

• Converts CSV files into RDF triples in the .nt serialization format.
• Supports both URI and literal values as objects.
• Adds language tags for English to string literals (lang tag can be modified for other languages).

How to Use

1. Input CSV File: Provide the path to your CSV file.
2. Run the Script: Execute the script csv2rdfConverter.py using Python 3.x. Make sure to have Python installed on your system.
3. Output: The script will generate an output file in the .nt format containing RDF triples. The output file will be named output.nt by default, but you can specify a different output file name if desired.

Requirements

• Python 3.x
• csv module (comes pre-installed with Python)

Example

Consider a CSV file named data.csv containing the following data:

subject,predicate,object
http://example.org/resource1,http://www.w3.org/1999/02/22-rdf-syntax-ns#type,http://example.org/class1
http://example.org/resource2,http://example.org/property1,"Literal value"

Running the script with this input will produce an output file named output.nt with the following content:

<http://example.org/resource1> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://example.org/class1> .
<http://example.org/resource2> <http://example.org/property1> "Literal value"@en .

Reporting Issues

If you encounter a bug or have a suggestion for improvement, please report it by following these steps:

1. Search for Existing Issues: Before creating a new issue, check the Issues section to see if your issue has already been reported.

2. Create a New Issue: If your issue is not listed, click on the "New issue" button. Fill out the issue template, providing detailed information such as:

   • A clear and concise description of the problem or suggestion.
   • Steps to reproduce the issue (if applicable).
   • Expected and actual results.
   • Screenshots or logs (if necessary).
   • Any additional context or configurations.

3. Use Labels: If possible, tag your issue with appropriate labels (e.g., bug, enhancement, question) to help categorize it.

4. Stay Updated: Once the issue is submitted, you can track updates, ask for clarification, or provide additional information as needed.

Thank you for contributing to improving the project!

License

Source code is made available under the BSD 3-Clause License. For questions, contact Darnelle Melvin.