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Ttl2html

screenshot of Ttl2html

Static site generator for Linked Data

Github

Overview

If you're looking to bridge the gap between RDF/Turtle data and the web, the ttl2html tool is a fantastic solution. Designed specifically as a static site generator for Linked Data, it seamlessly converts RDF/Turtle format into HTML files, making it easier to publish and manage your datasets online. The tool is built on the foundational principles of Linked Data, emphasizing the importance of identifying resources with HTTP URIs and resolving them on the web. This functionality is crucial for anyone looking to share Linked Data effectively.

With an intuitive setup process and a focus on customization, ttl2html empowers users to create professional and informative websites. Whether you are managing educational resources, datasets, or personal projects, ttl2html provides a streamlined approach to transform your data into a user-friendly web format.

Features

  • Easy Installation: Install the tool quickly using the command gem install ttl2html to get started without any hassle.

  • RDF/Turtle to HTML Conversion: Directly transform your RDF/Turtle formatted data into corresponding HTML files for seamless web publication.

  • Customizable Mapping: Configure property labels and title properties, allowing for a tailored presentation of your dataset.

  • Responsive ERB Templates: Utilize templates based on Bootstrap, ensuring that your generated site is not only functional but also visually appealing across devices.

  • SHACL Documentation Generation: Automatically produce documentation for your dataset schema using SHACL, simplifying compliance and understanding of your data structure.

  • Flexible Configuration: Set up a config.yml file to define your project's specifics, such as base_uri, output_dir, and site_title, providing complete control over the output.

  • Command Line Tool: Run the ttl2html command with various options for efficient execution, making it easy to integrate into workflows.

  • Award-Winning Tool: Recognized with the Technology Award at the Linked Open Data Challenge Japan 2024, highlighting its value and effectiveness in the field of data publishing.