A Catalog for Modern Data Products
A Centralized Catalog of Data, Access Protocols, and Applications for Building Powerful, Next-Generation Data Products.
The Data Catalog Advantage🔗
The Problem: Data Fragmentation
Enterprises struggle with disconnected data spread across various systems. This fragmentation hinders innovation, slows down development, and makes it impossible to build cohesive, intelligent data products.
The Solution: A Centralized Data Catalog
A Data Catalog provides a unified, queryable inventory of all available data assets, access methods, and applications. By creating a single source of truth, it accelerates development, promotes reuse, and empowers teams to build sophisticated data products with confidence.
Core Applications & Data Spaces🔗
Our ecosystem is composed of several interconnected applications, each representing a distinct data space within the catalog.
URIBurner
Publicly accessible data spaces for broad data exploration and integration.
Demo Environment
A sandbox with diverse public datasets for demonstrating platform capabilities.
Customer Support
Private, secure data spaces containing customer-specific information.
OnBoarding System
Manages product installers and onboarding documentation as distinct data assets.
Shop System
Powers e-commerce with data spaces for offers, carts, and payments.
Universal Data Access Protocols🔗
The catalog provides a rich variety of industry-standard protocols to ensure you can connect to your data from any tool or application.
Inside the Data Spaces🔗
A glimpse into the scale and diversity of entities within our primary data spaces, as registered in the catalog.
URIBurner Data Space
| Entity Type | Sample Entity | Count (Triples) |
|---|---|---|
| RDF Statement | Proxy IRI | 23,464,968 |
| Twitter Tweet | Status 1381... | 10,758,557 |
| Person | Anastasios V. | 4,160,832 |
| Annotation | Proxy IRI | 2,565,564 |
Demo Data Space
| Entity Type | Sample Entity | Count (Triples) |
|---|---|---|
| Transaction | 006ae8dd... | 200,000 |
| FraudLabel | 004de19a... | 200,000 |
| Company | Bechtelar-Lowe | 41,038 |
Shop, Support, & OnBoarding Data Space
| Entity Type | Sample Entity | Count (Triples) |
|---|---|---|
| DebugMessage | urn:products:message... | 2,092,628 |
| InfoMessage | urn:licgen:message... | 73,367 |
| ProductLicense | Product License | 5,552 |
| PurchasedItem | Purchased Item | 3,178 |
Data Product Development Lifecycle🔗
Leveraging the data catalog is a straightforward process designed for rapid development and value realization.
Discover
Browse the catalog to find relevant data spaces.
Connect
Use a documented protocol (SPARQL, JDBC, etc.).
Query
Retrieve the specific, contextualized data needed.
Assemble
Integrate data into your application or service logic.
Deliver
Launch your finished data product (API, dashboard, etc.).
Frequently Asked Questions🔗
A centralized registry acts as a single source of truth, directly addressing chronic enterprise issues like data silos and inconsistent information. It dramatically improves the discoverability of data assets, ensuring that developers and analysts can find what they need quickly. By standardizing descriptions of access protocols and applications, it promotes reuse, reduces integration costs, and establishes a clear foundation for data governance and security.
A registry becomes a powerful Data Catalog when its contents are described in a structured, machine-readable format. We achieve this using standard RDF vocabularies like VoID (Vocabulary of Interlinked Datasets). This turns a simple list into a queryable knowledge graph about your data. For instance, the catalog can describe each dataset's title, its SPARQL endpoint, available access protocols, and even statistics like the total number of triples, creating a rich, searchable inventory for both humans and automated tools.
A Data Catalog is the essential "design-time" tool for building "run-time" Data Products. Think of the catalog as a well-organized workshop: it contains an inventory of all available parts (datasets), tools (access protocols), and blueprints (application logic). A data product developer uses the catalog to discover, evaluate, and select the precise components they need. This allows them to rapidly assemble and deliver a finished Data Product—such as a specific API, a real-time dashboard, or an AI-powered service—that is reliable, well-documented, and built from governed, high-quality data sources.