LDG is like a map for your data. Point it at any database and it instantly draws a picture of how the different pieces of information are connected, helping you navigate complex datasets at a glance.
Important
Analyzing the structure of an arbitrary SPARQL endpoint is inherently computationally expensive. LDG performs multiple discovery queries to identify classes, relationships, and datatypes.
- Endpoint Support: The system is primarily optimized for QLever endpoints. Other SPARQL implementations may experience timeouts or high memory usage on large datasets.
- Default Limits: By default, LDG limits discovery to the top 10 classes to ensure responsiveness.
- Customization: You can adjust the class limit, concurrency, and other parameters in the Settings dialog within the application.
WebVOWL/LD-VOWL was a powerful way to understand how things are connected in an RDF knowledge graph without having to explore the data manually.
This version is based on the innovative ideas of the original authors (Marc Weise, Steffen Lohmann, and Florian Haag). However, as the original codebase was more than a decade old, it has been refactored (probably more rewritten) using Antigravity. The entire application was rebuilt from scratch using Web Components, modern D3.js v7, and Sigma.js.
We enjoyed the process of breathing new life into this project and I hope you enjoy using it!
LDG requires Node.js (v16+) to be built.
- Download and install Node.js.
- Clone this repository.
- Run
npm installin the root directory to install the dependencies. - Run
npm run devto start the local development server. - Run
npm run buildfor a production build.
To get a production build, run npm run build. After the build is finished, the results will be inside the dist directory.
LDG is licensed under the MIT License. See LICENSE.txt for more details.