Getting Started with RDF & SPARQL
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.
This beginner-level training teaches the foundational concepts of Stardog Database Administration. This training will review user interfaces, Stardog Studio and CLI, and basic data base operations like how to create/load/drop, backup/restore, repair/optimize, view/change db status, and view/kill running queries. The training will conclude with an overview of Stardog server administration and how to configure memory, log, and run as a Linux service.
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.
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.
Installation & Setup
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.
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.
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.