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BIOMEDIN 274: Seminar on Linking Open Data and Knowledge Graphs - Methods and Challenges

In this course, we will discuss recent advances in data publishing and integration from the viewpoint of Linked Data and Open Data. Linked Data is data published according to certain principles to make it easier to find, co-reference and query/integrate data published across different sources and accessible through standard Web protocols. These principles have been found useful and been applied to data from the Biomedical domain, but also in the domain of Open Government Data, or in the Library domain. In this seminar, we will discuss recent advances in search and integration of heterogeneous data source from these domains, by interlinking them with formalized background knowledge graphs and ontologies, based on seminal papers and results from our own research. We will learn about principles and methods, and also about common challenges. The seminar will be held as a mix of lectures, guest lecture, and student presentations/discussions. As pre-reading, I recommend the following book chapter from a lecture at the Reasoning Web Summer School 2017: S. Neumaier, A. Polleres, S. Steyskal, and J. Umbrich. Data integration for Open data on the Web. In G. Ianni, D. Lembo, L.E. Bertossi, W.Faber, B. Glimm, G. Gottlob, and S. Staab (editors), Reasoning Web. Semantic Interoperability on the Web (Reasoning Web 2017), volume 10370 of Lecture Notes in Computer Science (LNCS), pages 1--28. Springer, Lodon, United Kingdom, July 2017.
Terms: Spr | Units: 1
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