Getting Started with RDF & SPARQL
Apr 16, 2021, 1 minute read

This beginner-level training teaches the basics of RDF graphs and the SPARQL query language. Review the basics of RDF data including graph, triples, nodes, IRIs, prefixes, datatypes, and Turtle. By the end of this training, you will understand how to construct SPARQL queries, demonstrate the use of SPARQL to create or update RDF data, and know-how to work with named graphs.

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Architectures
Apr 16, 2021, 1 minute read

This beginner-level training teaches the basics of Stardog Architectures. During this training, you will gain an understanding of Stardog deployment options including single nodes and clusters. We’ll review the Stardog ecosystem including typical patterns within different Stardog architectures, common architecture design choices, and the fundamentals of Stardog Cloud and Stardog Connectors.

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Security
Apr 2, 2021, 1 minute read

This beginner-level training teaches Stardog’s security model in detail. During the training, you will become familiar with Stardog’s Role-Based Access control implementation, including creating new Users and Roles, and how to assign permissions to each. Learn the specifics of Named Graph Security, specifically how named graph permissions work and how to restrict access to them, as well as the basics of LDAP integration. By the end of the training, you’ll understand the requirements for running Stardog with SSL and how to deploy Stardog securely.

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Installation & Setup
Feb 22, 2021, 1 minute read

This beginner-level training teaches the installation and set-up of Stardog and Stardog Studio on your system. Learn steps on how to install Stardog and Stardog Studio using OSK, Linux & package managers (Debian or RPM), Docker, or Windows. After the installation and set-up is complete, review the run process including how to start the server, connect to it from Studio, and how to shut down the server.

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Getting Started With SPARQL
Jul 7, 2019, 1 minute read

Join this Stardog training webinar to learn the basics of SPARQL. This training is intended for those who are brand new to working with SPARQL, the core query language of Stardog’s Enterprise Knowledge Graph.

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Virtual Graphs
Jun 7, 2019, 1 minute read

This beginner-level training will teach how to define and apply Virtual Graphs, including reviewing the new data source feature, Virtual Graph mappings, applying virtual transparency, leveraging named graph aliases, and applying caches to Virtual Graphs. By the end of this training, you will fully understand virtual mapping to data sources and how Virtual Graphs interact with other features.

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Tips For SPARQL Query Optimization
Jun 7, 2019, 1 minute read

Watch this Stardog Webinar to learn tips and tricks for writing performant SPARQL queries. The webinar is intended for those who are familiar with the SPARQL query language, but want to gather more practical experience in diagnosing and addressing performance problems. It will also introduce the new Stardog Studio visualization capabilities helping with these tasks.

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SPARQL Query Types and Key Stardog Features
Jun 7, 2019, 1 minute read

Gain hands-on experience with SPARQL, the RDF query language that’s central to Stardog with this training intended for beginners. Watch the webinar to learn the basic query types of SPARQL and some of the key features of Stardog so you can get the most out of your knowledge graph. Familiarize yourself to the SPARQL language Understand different types of queries and when to use them Explore path queries – unique to the graph space

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Querying Stardog with GraphQL
Jun 7, 2019, 1 minute read

Watch to learn how to use GraphQL to query Stardog’s knowledge graph. No GraphQL or Stardog expertise required!

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Modeling
Jun 7, 2019, 1 minute read

This beginner-level training teaches the basics of successful data modeling for developing an Enterprise Knowledge Graph. Learn about the various types of data models used across the graph domain with a specific focus on ontology models, a particular model type frequently used in knowledge graph development. Review the step-by-step process of model development and learn the practical considerations for ontology development, including use of naming scheme, ontology modularity, and versioning, and testing and debugging.

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