Visualization FTW

Apr 19, 2018, 4 minute read
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We take a look at data visualization tools in Stardog for exploiting the enterprise knowledge graph.

Unifying data into an enterprise knowledge graph provides an unparalleled view into data, relationships, and overall quality of information across the enterprise. But how do we actually see that? Analysts, product managers, and other stakeholders are unlikely to write graph queries directly, so what options do we have? Let’s walk through some of the options.

Enterprise Viz Tools

Stardog currently works with Tableau and Linkurious. Let’s look at those in turn.


Tableau empowers users to create and distribute dashboards to visually analyze data, including a Stardog knowledge graph. In Tableau, you can use the drag and drop interface to easily create different views from multiple databases. Once the views have been generated, they can be shared with others by publishing them to a Tableau Server. Stardog supports Tableau as a Web Data Connector.

To get started, open up Tableau and select Web Data Connector. In the pop-up, enter the URL:, which will open up the interface to configure the Stardog connection.

Once you have the connector in place, you are off to the races with building Tableau dashboards.

We can work with the result set in a Tableau sheet where the data can be aligned to measures and visualized using one of the charts and graphs available.


Linkurious is a graph visualization tool that allows users to identify and investigate insights hidden in complex connected data. Users can query, visualize, and collaboratively investigate data. Visualizations can be built and shared, with both navigation and design applied to customize which nodes and edges users see. Without having to write any code, the visualizations can be customized from a design perspective, showing certain nodes with applied icons and colors to highlight areas of interest.

Open Source Libraries

These enterprise tools have a lot of capability out of the box and can be used by analysts and data scientists to quickly bring the value of the knowledge graph to stakeholders. There will be other times when you need specialized visualizations. We’ve seen that knowledge graphs, enriched with ontologies and rules, can present a lot of information. Sometimes you just want to visualize links in a certain direction or only relevant nodes that meet some criteria (e.g. only baselined data).

We’ve used a variety of open source tools to build custom visualizations to meet requirements. In most cases, this starts with the stardog.js library, which provides a modern JS client to Stardog.


D3.js is a JS library for manipulating documents based on data. D3 helps you bring the knowledge graph to life using HTML, SVG, and CSS. D3 allows you to bind arbitrary data to a Document Object Model (DOM) and then apply data-driven transformations to the document. Often we want a visual representation of the nodes and edges associated with specific objects. Using a soon to be released Stardog D3 JS implementation and stardog.js, we can query the graph and view the relationships.

This approach lets us quickly build custom visualizations like the one we built to see objects within the requirements hierarchy for NASA’s Mission to Mars.


RaphaëlJS is a lightweight JavaScript framework that uses the SVG W3C Recommendation and VML as a base for creating visualizations. This allows the objects you create to also be a DOM object which gives you the flexibility to attach event handlers or modifiers. We use RaphaëlJS for showing dependencies between parent and child. Similar to the D3 implementation, we used stardog.js to query the graph and deconstructed the results in that model that RaphelJS can consume.

Again, looking at an example from NASA, we can see how functional dependencies are related in the Mission to Mars.

Other Tools

We’ve also used Gephi for some early quick wins on what can be possible with a unified knowledge graph. Gephi is an open-source visualization software package written in Java, which allows the user to interact with graph data.

Below is an example from a recent graph we were working on. The nodes with darker shades of green show the nodes that are more highly connected than the lighter shades of green. This view was generated by running a query in Stardog Studio and exporting it to CSV and then importing into Gephi to build the visualization.

As you can see in the screenshot above, the Gephi visualization can highlight the complexity of the data and help drive early conversations about where to spend resources building further visualization products.


In this blog post, we looked at how bringing together data into a unified knowledge graph opens up a world of possibilities on data visualization. We’ve only scratched the surface and with GraphQL support and path queries in Stardog 5, we’re excited to build even more visualizations. Whether you’ve selected an enterprise tool, or want to build something custom, we’re always excited to work with customers to bring out the value of Stardog to build an enterprise knowledge graph.

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