RDFox IDE
& Graph Visualization Tool

Explore, query and visualize your graph data in RDFox with gdotv.

A Purpose-Built IDE for RDFox Developers

For practitioners working with RDFox, gdotv provides a comprehensive development environment well-established for RDF and SPARQL workflows.

The gdotv IDE supports core editorial capabilities such as syntax highlighting, autocomplete suggestions, integrated SPARQL documentation, and systematic prefix management, facilitating precise and efficient query authoring. Beyond these, gdotv incorporates advanced validation mechanisms, including SPARQL Query Guardrails, which assess query consistency with respect to the underlying ontology and schema constraints and is an essential feature when working with RDFox’s rule-based reasoning and materialization capabilities.

From a data interaction perspective, gdotv enables multiple complementary representations of RDF data. Graph visualization supports nodes, edges, and literals with full edit operations (insertion, deletion, and modification), while tabular views provide a structured alternative for inspecting query results. The system further introduces a unified data model abstraction, derived from both ontological triples and instance-level inferrings, enabling a coherent conceptual view over the dataset.

gdotv’s Data Explorer component allows users to construct queries through a no-code graphical interface by defining paths and constraints, which is particularly valuable for systematically exploring inferred and explicitly asserted knowledge in RDFox-managed graphs.

In certain scenarios, RDFox adopts behaviors that diverge from the standard W3C SPARQL specification, and in such cases, gdotv is explicitly designed to recognize and accommodate these differences.

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RDFox

Oxford Semantic Technologies, a Samsung Electronics subsidiary

Query languages supported by gdotv: SPARQL

Learn more about RDFox

An Overview of RDFox

RDFox is a high-performance, in-memory RDF triplestore and reasoning engine developed by Oxford Semantic Technologies. It is designed to support efficient storage, querying, and logical inference over large-scale RDF datasets. RDFox distinguishes itself through its support for parallelized Datalog-based reasoning, enabling the materialization of inferred knowledge using user-defined rules in combination with standard RDF semantics.

The system provides full support for SPARQL querying, including extensions for reasoning-aware query answering. Its in-memory architecture allows for low-latency query execution and high throughput, making it suitable for both analytical and real-time applications. RDFox supports incremental reasoning and updates, allowing changes in the dataset to be efficiently propagated through the inference layer without requiring full recomputation.

A major use case of RDFox is knowledge graphs

In terms of deployment, RDFox can operate as an embedded library or as a standalone server, offering flexibility across different system architectures. It is commonly applied in domains requiring rich semantic reasoning, such as knowledge graphs, data integration, and enterprise data management, where both explicit and inferred knowledge must be queried in a unified manner.

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What’s Possible with RDFox + gdotv

Easy Installation & Setup

Effortlessly integrate gdotv with your RDFox graph database with a simplified plug-and-play database connector. The gdotv database client provides straightforward database connection and configuration instructions to get you started in less than a minute.

This RDFox IDE is available to download for Windows, macOS, and Linux with a one-click installer to get you started instantly.

Connecting to RDFox with the gdotv database visualization tool is as easy as 1-2-3!

Manage all your database connections and queries from one central console.

Centralized Connection Management

gdotv can be used to query and compare data from a huge range of graph database vendors – simultaneously! We don’t just work with RDFox: gdotv data visualization tools fully integrate with various other graph technologies, including all Apache TinkerPop™ compatible graph databases and most LPG and RDF providers.

gdotv is fully compatible with query languages like Gremlin, Cypher, Google SQL, SQL:2023, SPARQL and more. Using an intuitive UI, you can switch between your connections and queries seamlessly.

Customizable Data Visualization

You can create custom visualization rules for your graph database with gdotv to determine the look and feel of your data.

Our database client boasts easy-to-configure style options that you can use to customize vertices and edges based on their labels and property values.

You can choose any color, size, or background image and adjust other elements to match your preference.

A sample graph display in gdotv using loading custom image file URL from node properties

The Graph Data Explorer enables no-code path exploration directly against your RDFox graph database in just a few clicks

No-Code Data Exploration with the gdotv Graph Data Explorer

Use the built-in gdotv Graph Data Explorer to navigate your RDFox data without using queries.

The Graph Data Explorer allows you to define path patterns to query from your data, using filters on both your vertices and edges. Elements in the declared path can be filtering according to their label, direction, and property values, allowing you to perform complex path-pattern searches with no code.

Instantly Load & View Your Data Model

Understanding and verifying your data schema is critical component of graph management. This is why gdotv provides an overview of your data structure with the data model view.

For RDFox, there is no need to provide a data model, as gdotv is able to infer the schema directly from the data itself. This is always just a click away, meaning that you always have an bird’s-eye view of your vertices, edges, and properties right at your fingertips.

Access your data model

Create, update or delete nodes, edges, and properties interactively

Modify Your RDFox Graph Data Directly within gdotv

Want to adjust something in your graph? Take a hands-on approach and manage your RDFox graph directly.

Using gdotv, you can directly create, modify, and delete the edges and nodes – as well as modify the properties associated with them – allowing you to make changes on the fly.

Take Advantage of Syntax Validation

Using gdotv language highlighting and syntax checking for SPARQL makes your code easier to understand and visually parse, warning you of any error that would prevent it from executing against your RDFox instance.

Intuitive interface with syntax highlighting and validation

gdotv’s SPARQL query guardrails detect a typo by checking queries against the graph structure

Take Control of your Queries with SPARQL Query Guardrails

Since RDF is fundamentally schema-optional, gdotv doesn’t enforce any schema against your graph. It will, however, check your queries against the inferred schema, meaning it will automatically generate warnings if it detects potential ontology clashes.

This gives you additional insight into malformed queries, even when they execute normally against your RDF triplestore.

Visualiztion Optimized for RDF

gdotv offers graph visualization especially developed for RDF triplestores.

The nodes and edges are detected from your query results, and any literals will be interpreted as properties. To improve readability, gdotv has built in IRI shortening and prefix handling.

You can customize your graph labels further using inferred schema from the graph, such as via RDFS statements.

gdotv automatically performs prefix handling and IRI shortening

gdotv’s built-in documentation for SPARQL, right at your fingertips

State-of-the-Art SPARQL Editor

The gdotv SPARQL code editor is the most powerful available – it offers data schema-accurate auto completion and embedded official documentation for SPARQL to give you all the information and suggestions you need to write your RDFox queries faster and more effectively.

RDFox + gdotv Blog Posts

March 26, 2026

The Weekly Edge: Read S3 Data with Cypher, Graph in Fabric GA, Epstein Files Graph Viz, & More

Bryce Merkl Sasaki

March 17, 2026

Announcing SPARQL Query Guardrails, Dashboarding, Query Editor Upgrades, & More [v3.53.111 Release Notes]

Amir Hosseini & Geoff Storbeck

February 27, 2026

The Weekly Edge: BigQuery Goes Graph (Privately), a GQL Playground, a Knowledge Graph of Your Vibe Code & More

Bryce Merkl Sasaki

February 12, 2026

SPARQL Query Guardrails: Making Your SPARQL Queries ETL-Ready

Amir Hosseini

Frequently Asked Questions (FAQs)

How can I get started with RDFox and gdotv?

Getting started with RDFox and gdotv is easy. It’s just one simple installation, available on Windows, macOS and Linux. No prerequisites, additional configuration or installation required. You can get started in seconds.

gdotv automatically detects your connection setting requirements based on your database hostname and prompts you for the required information for an easy onboarding experience.

Want a step-by-step walkthrough? Make sure to check out our demo, Get Started with RDFox + gdotv on YouTube.
What's the advantage of using RDF over LPGs?

Graph databases typically fall into two models: Resource Description Framework (RDF) and Labeled Property Graph (LPG).

The RDF model is used by RDFox and refers to a highly standardized form of data management. Information is stored as a series of directed “triple” statements connecting a subject, predicate and object together. In addition, various languages built on RDF (such as RDFS and OWL) allow the construction of sophisticated ontologies and semantic reasoning.

The LPG model covers a broad class of databases that use nodes, edges, properties and labels to represent graphs. They are optimised for real-time use and excel in applications like fraud detection, social network analysis, and recommendation algorithms. There are a wide range of methods to enforce schema compliance, with flexible conventions and definitions.

RDF is a rigorous framework with well-established vocabularies. The highly developed semantic structure makes RDF a powerful tool for inferring relationships and new insights from data. The high level of standardization in RDF also makes it ideal for inter-compatibility, as data from disparate sources can be integrated with ease. This makes RDF ideal for applications in large knowledge graph construction and research.
How do the SPARQL query guardrails work?

A SPARQL query engine performs no semantic inference over the stencil you define; it simply evaluates patterns and returns the nodes and edges that match them. As a result, a query can be syntactically valid, executable by any compliant engine, and even return results, while still being semantically meaningless with respect to the underlying data model.

In gdotv, SPARQL query guardrails surface this problem before execution and even while the query is being written, giving you immediate, context-aware guidance. The system can infer, for example, if a predicate implies a specific kind of subject or object from those provided by the query.

Read a detailed discussion from Amir here.
What graph data visualization use cases do gdotv customers implement most often?
Organizing data derived via powerful data visualization tools have several real-life applications. Graph visualization and analysis resources allow users to make informed decisions based on actual data.

Here are a few examples of the type of companies or clients that can leverage RDFox along with the robust data visualization aspect offered by gdotv:

Data scientists and managers: Visual data analysis allows users to uncover and understand emerging patterns and relationships between data points, discover valuable insights to make informed decisions on ways to transform business processes.

Cybersecurity groups: Build security graphs to represent protected assets, infrastructure, code dependencies or networks and visualize the connected relationships throughout the organization.

Business intelligence analysts: Create customized reports and visualizations that can be easily executed for analysts to investigate and communicate on interaction between business data points.

Fraud detection: Detect fraud patterns by modeling relationships between transactions and financial actors, then interactively visualize graph data to uncover and present potentially suspicious behavior.
How does gdotv secure my data?

gdotv Desktop runs locally on your device – no deployment needed and no handing over your data to a third-party system. Everything happens within your organisation’s network, and we have no access to your data.

gdotv Web versions run within your own environment, providing the same security benefits.

It’s easy to install and configure too: our setup wizard gets you connected to your graph database in seconds.
Can I connect more than one database at a time?

Yes! Whether you’d like to access multiple RDFox instances, or interact with other graph technologies at the same time, gdotv doesn’t limit you to a single database. You can establish as many connections as you like from within the intuitive UI and seamlessly switch between them.

Connecting is easy, and there’s no need to manage multiple vendor-specific user interfaces. With gdotv, query and compare results from all your RDF and labeled property graph databases under one umbrella.

gdotv: The RDFox IDE

Turn your graph data into connected insights when you use gdotv to query, explore, and visualize your RDFox graph database.

Sign up for a free trial today and discover how gdotv amps up your productivity as the perfect RDFox IDE and graph visualization tool.

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RDFox IDE& Graph Visualization Tool