Ontotext Academy

Self-paced learning paths about GraphDB and semantic technology, designed for Ontotext partners, clients and GraphDB users who want to build knowledge graphs and put them into action.

Learning Paths For Different Audiences

GraphDB Knowledge Graph Engineer

Using the W3C RDF-related standards to get the most out of Knowledge Graphs. 

GraphDB Developer

Creating the applications that take advantage of the knowledge graphs the Knowledge Graph Engineer has designed.

GraphDB Operations

Efficient maintenance of the back end systems. 

GraphDB Knowledge Graph Engineer Learning Paths

Explore curated sets of courses for a tailored learning experience

Intro to Semantic Technologies

An overview of graphs, knowledge graphs, RDF standards, triplestores, and how applications get built around these.

Semantic Models

RDF data model and syntax, building schemas and ontologies, the Linked Open Data Cloud, and how to validate data with SHACL.


Writing SPARQL queries to retrieve, create, and update data using filters, functions, aggregation, property paths, and more.


Does this training cost anything?

  • No, this is a self-paced learning path experience with free access. You will need to register for the learning system.

What is the difference between the Academy and the free resources on your website?

  • There are a couple of advantages to the Academy compared to the freely available Ontotext documentation and webinars. These training paths are designed with a specific audience profile in mind:
    • Knowledge Graph Engineers, who are designing the data models with RDFS and maybe OWL, extending standard data models if necessary, developing SHACL shapes to ensure data quality, and identifying which data sets should be combined to create knowledge graphs for their enterprise's applications.
    • Application Developers who are using their JavaScript framework, or their preferred programming language, to efficiently query, add data to, and delete data from knowledge graphs stored in GraphDB on the backend of their system. They are not interested in rich ontology modeling, but they want to know about the various APIs that GraphDB supports and which are best for what.
    • DevOps staff, who want to know how to configure a set of clusters to support the applications created by the developers, especially if those applications are being used by thousands of users.

What are the prerequisites for this training?

  • This training is meant to provide data scientists, researchers, product managers and developers with the theoretical and practical knowledge necessary to design a small proof-of-concept project that demonstrates the utility of Semantic Technology and a graph database.

    Although you will need to have some basic understanding of Semantic Technology and programming and query languages, no detailed knowledge is required. All advanced concepts exposed in the training will be explained in sufficient detail.

How long does the training last?

  • Each learning path consists of three or four courses, and each course typically takes a half a day or a little more.

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