Fr., 28.10.2022 13:00 - 18:00 Uhr, Ort: (IM) SR 007
Art/Form
Literatur
[1] Tom Heath and Christian Bizer. Linked Data: Evolving the Web into a Global Data Space. Synthesis Lectures on the Semantic Web: Theory and Technology, Morgan & Claypool. 2011
[2] Bob DuCharme. Learning SPARQL: Querying and Updating with SPARQL 1.1. O'Reilly Media, Inc. 2013
[3] Panos Alexopoulos. Semantic Modeling for Data. O'Reilly Media, Inc. 2020
[4] Mayank Kejriwal, Craig A. Knoblock, Pedro Szekely. Knowledge Graphs (Adaptive Computation and Machine Learning series). MIT Press. 2021.
Skills / Knowledge The students acquire a systematic understanding of publishing and sharing data on the web. They know basic and advanced models and formats for representing data on the web as knowledge graphs, the principles for achieving data interoperability through ontologies, and advanced technologies for querying the data. Abilities The students can identify, understand, and access/query data published on the web (REST, SPARQL). They can also publish their data in an interoperable way exploiting existing and designing their ontologies to describe the data. They can combine data from different data sources into a single knowledge graph and query it. Competencies The students have the competence to select appropriate technologies for publishing and consuming data on the web, design ontologies to describe the data, and design and execute queries (SPARQL) on top of the data.
This module focuses on the principles of sharing data on the web through REST and Linked Open Data APIs. It shows suitable data formats for publishing data on the web, explains the role of ontologies and data vocabularies in improving data interoperability, and presents how to consume data using the SPARQL query language.
