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68704-01 - Seminar: Semantic Web & Linked Data 3 CP

Semester spring semester 2023
Course frequency Irregular
Lecturers Sepideh Alassi (sepideh.alassi@unibas.ch, Assessor)
Content A formalized computable representation of human knowledge has long been a goal of data science. Several approaches have been proposed since the dawn of computer science and artificial intelligence to create a web of data instead of web of documents. In this course we will introduce the most recent approaches based on the semantic web standards (RDF, RDFS, RDF-star, SPARQL, SPARQL-star, and OWL). We will then describe how these standards can be used to achieve the goals of a distributed shared knowledge infrastructure, Linked Open Data (LOD).

The course guides students through the introductory stages to create LOD-based knowledge graphs in order to make every piece of information machine-readable.
Learning objectives At the end of this course, the students
(1) understand what Linked Data is, and are able to make use of the concepts and goals of the Linked Open Data movement
(2) understand the fundamental ideas of knowledge representation (entities, concepts, instances, ontologies, etc)
(3) are very familiar with the Semantic Web standards (RDF, RDFS, RDF-star, SPARQL, SPARQL-star, and OWL)
(4) know about the linked open data storages and have practical experience of storing their project data as RDF triples to create a knowledge graph
(5) can query and visualise the knowledge graph to analyse data
Bibliography - A Developer’s Guide to the Semantic Web, by Liyang Yu
- Programming the Semantic Web, by Toby Segaran, et. al.
- Semantic Web for the Working Ontologist, by Dean Allemang, and Jim Hendler
Comments Students should bring their own laptop to the course.

 

Admission requirements The number of participants is limited. In case of over-subscription, students of Digital Humanities will be admitted preferentially.

No-prior knowledge about semantic web is required.
Language of instruction English
Use of digital media No specific media used

 

Interval Weekday Time Room
wöchentlich Thursday 16.15-18.00 Kollegienhaus, Hörsaal 119

Dates

Date Time Room
Thursday 23.02.2023 16.15-18.00 Kollegienhaus, Hörsaal 119
Thursday 02.03.2023 16.15-18.00 Fasnachstferien
Thursday 09.03.2023 16.15-18.00 Kollegienhaus, Hörsaal 119
Thursday 16.03.2023 16.15-18.00 Kollegienhaus, Hörsaal 119
Thursday 23.03.2023 16.15-18.00 Kollegienhaus, Hörsaal 119
Thursday 30.03.2023 16.15-18.00 Kollegienhaus, Hörsaal 119
Thursday 06.04.2023 16.15-18.00 Ostern
Thursday 13.04.2023 16.15-18.00 Kollegienhaus, Hörsaal 119
Thursday 20.04.2023 16.15-18.00 fällt aus
Thursday 27.04.2023 16.15-18.00 Kollegienhaus, Hörsaal 119
Thursday 04.05.2023 16.15-18.00 Kollegienhaus, Hörsaal 119
Thursday 11.05.2023 16.15-18.00 Kollegienhaus, Hörsaal 119
Thursday 18.05.2023 16.15-18.00 Auffahrt
Thursday 25.05.2023 16.15-18.00 Kollegienhaus, Hörsaal 119
Thursday 01.06.2023 16.15-18.00 Kollegienhaus, Hörsaal 119
Modules Modul: Creating, Analyzing and Visualizing of Data (Master's degree subject: Digital Humanities)
Modul: Methoden der Gesellschaftswissenschaften (Master's Studies: European Global Studies)
Assessment format continuous assessment
Assessment details There is no examination for this course.

Students have to submit solutions to 4 exercises given in the course before the specified deadline. The total grade accumulated from the exercises will consist 40% of your final grade.

Students should define a linked open data project and apply the learned techniques to complete this project and create a knowledge graph. A final report should be written for the project that describes the data modelling, knowledge graph creation, as well as analysis of the data through defining questions and answering them by querying the graph. The final project consists 60% of your final grade.

Note: students should work on exercises and the final project in groups of 3-4.
Assessment registration/deregistration Reg.: course registration; dereg.: not required
Repeat examination no repeat examination
Scale Pass / Fail
Repeated registration as often as necessary
Responsible faculty Faculty of Humanities and Social Sciences, studadmin-philhist@unibas.ch
Offered by Digital Humanities Lab

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