Knowledge representation as linked data : Tutorial
| Autor: | Joachim Van Herwegen, Pieter Heyvaert, Ben De Meester, Ruben Taelman, Anastasia Dimou |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Information retrieval
Knowledge representation and reasoning Process (engineering) Computer science 020204 information systems 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing 02 engineering and technology Linked data Reusability |
| Zdroj: | CIKM'18: PROCEEDINGS OF THE 27TH ACM INTERNATIONAL CONFERENCE ON INFORMATION AND KNOWLEDGE MANAGEMENT CIKM |
| Popis: | The process of extracting, structuring, and organizing knowledge requires processing large and originally heterogeneous data sources. Offering existing data as Linked Data increases its shareability, extensibility, and reusability. However, using Linking Data as a means to represent knowledge can be easier said than done. In this tutorial, we elaborate on how to semantically annotate data, and generate and publish Linked Data. We introduce [R2]RML languages to generate Linked Data. We also show how to easily publish Linked Data on the Web as Triple Pattern Fragments. As a result, participants, independently of their knowledge background, can model, annotate and publish Linked Data on their own. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|