COURAGE knowledge graph
The COURAGE knowledge graph contains data about cultural opposition under socialism focusing on collections, and describing also persons, person roles, organizations, groups, events and featured collection items. The graph connects these entities and also enables locating them on the map. Graph content was collected by researchers from 15+ countries and includes text in 15 languages.
The technology provided by SZTAKI DSD can be easily generalized and adapted for collaborative building and maintenance of knowledge graphs in various application domains. We can also provide help in building schemas, ontologies for knowledge representation.
Poems smuggled out of prison, samizdat books the size of a hummingbird, university samizdats, apartment theaters, and secret police files - the exhibition Risk Factors presents documents and artefacts from the cultural opposition under communism by selecting items from the COURAGE registry.
The project provides three types of learning material: for high schools characteristic terms and phenomena such as censorship, samizdat etc. are introduced with illustrations.
For universities we provide syllabi containing links, readings and tasks for self-learning. Tutors may create or customize their own syllabi using our system.
The Peripatos walking app can be downloaded on our page about education. After installation, one can download walking tours for four cities, and then make sightseeing from the viewpoint of cultural opposition.
The games provide interactive tasks for familiarizing ourselves with characteristic terms of the era.
All previously mentioned and further results of the project are available on the COURAGE homepage: cultural-opposition.eu.
About the architecture, implementation and content of the knowledge graph one can consult the second chapter of the COURAGE Handbook. It is to be highlighted, that all data was stored as linked data during the project. Of course, this was not revealed for the more than 100 humanities researchers who submitted their research findings directly into the triple store via ordinary web forms. The graph database proved to be very useful for showing relationships between entities and the SPARQL query language helped to create and run complex graph queries. The RDF format made it very easy to manage textual descriptions in 15 languages simultaneously.
Finally, a small excerpt of the knwoledge graph is shown as an example, and a collage demonstrating the variety of cultural items covered by our research.