NFDI4Culture Metadata API
Metadata of all resources as Linked Open Data
The NFDI4Culture portal offers all content as Linked Open Data over this RESTful API. The API implements the Hydra-Specification of the W3C Hydra Community Group. The semantic description of this API can be retrieved by clients via the Hydra documentation file (JSON). Each metadata record offered via this API can also be retrieved in one of following machine-readable LOD serializations. The API is the basis for the Culture Research Information Graph, which together with the Culture Research Data Graph forms the Culture Knowledge Graph (for more details see this presentation).
Persistent Identifier: <https://nfdi4culture.de/id/E4697>
Knowledge Graphs - Foundations and Applications
Retrieve record as:
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- https://nfdi4culture.de/news/knowledge-graphs-foundations-and-applications.html
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- Knowledge Graphs - Foundations and Applications
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- Knowledge Graphs - Foundations and Applications
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A Knowledge Graph is a structured representation of knowledge used to provide a comprehensive and interconnected view of a specific domain. The FAIRification process of research data relies heavily on Knowledge Graphs, which serve as foundational elements of modern information systems. However, for individuals lacking a computer science background, comprehending the concept of Knowledge Graphs can be challenging, preventing them from creating or participating in its development. To overcome this, we suggest taking the OpenHPI course "Knowledge Graphs – Foundations and Applications" for anyone interested in the subject.
This programme will provide all the essential knowledge needed to design, execute, and utilise Knowledge Graphs. The course will concentrate on fundamental semantic technologies, such as the principles of knowledge representation and symbolic AI. This encompasses encoding information via RDF triples, representing knowledge through ontologies using OWL, performing efficient queries on Knowledge Graphs by means of SPARQL, expressing latent knowledge in vector spaces, and utilizing knowledge graphs in sophisticated information systems, such as semantic and exploratory search. Furthermore, this course will discuss the role of knowledge graphs in artificial intelligence and machine learning, as well as their potential to improve the explicability and trustworthiness of "black box" deep learning models such as Chat-GPT.
Detailed information about the course can be found here: https://open.hpi.de/courses/knowledgegraphs2023
Participation is free of charge.
Come and join us!
Harald Sack, Tabea Tietz, Oleksandra Bruns, Mahsa Vafaie, Mary Ann Tan
- datePublished
- 2023-10-11T10:00:00+02:00