GraphDB is Ontotext’s leading RDF database for creating knowledge graphs. The following video fundamentals will guide you in your first steps:
- Learn the fundamentals of W3C standards for RDF databases in the first three videos: RDF & RDFS, SPARQL and ontology.
- Follow with GraphDB installation and set-up instructions to start with your first query or load your datasets.
- Finally, get the maximum of GraphDB functionality: understand its reasoning strategies; RDFRank, Geo-spatial and full-text-search extensions; and GraphDB Connectors.
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1. Overview of RDF & RDF(S)
This video introduces you to RDF as a standardized format for graph data representation, to what RDFS adds to it as well as how to use it by easy-to-follow examples from The Flintstones cartoon.
2. Overview of SPARQL
This video covers the basics of SPARQL – a SQL-like query language for RDF data. It is recognized as one of the key tools of Semantic Technology and is a W3C standard. The module aims to provide you with sufficient knowledge to create your first RDF graph and run your first SPARQL queries.
3. A Look at Ontology
This video focuses on ontologies: what is an ontology, what kind of resources does it describe and what are the benefits of using ontologies. Ontologies are the core of how we model knowledge semantically.
4. Installing GraphDB
This video covers the different GraphDB distributions and guides you through the steps of installing GraphDB.
5. Workbench and REST API
In this video, we provide a brief overview of GraphDB Workbench and it’s main functionalities. GraphDB Workbench is an administration web-based interface similar to the RDF4J Workbench Web application but it’s much easier and more intuitive to use and offers more functionality.
6. Loading Data
This video shows you how to load data in GraphDB with the help of GraphDB Workbench, Parallel LoadRDF Tool, Preload Tool or OntoRefine. Data is the most valuable asset and GraphDB is designed to store and enhance it.
7. Reasoning and Rule Set Strategies
This video outlines the main strategies of getting new information from your data as well as the rule sets used by GraphDB. The three different reasoning strategies discussed are forward chaining, backward chaining and hybrid chaining and they support various GraphDB reasoning optimizations.
8. Data Virtrualization
This video focuses on the data virtualization in GraphDB, which enables direct access to relational databases with SPARQL queries and eliminates the need to replicate data. The implementation exposes a virtual SPARQL endpoint, which translates the queries to SQL using declarative mapping.
9. GraphDB Plugins
This video introduces you to the GraphDB Plugins, which are externally provided libraries allowing developers to extend the engine. They can synchronize their internal state over the public plugin API and handle the execution of registered tuple patterns.
10. GraphDB Connectors
This video presents the GraphDB Connectors, which provide automatic synchronization to external search systems like Lucene, Solr or ElasticSearch. They are responsible for mapping the RDF model to the supported document-centered model of these systems and providing automatic updates.