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| Semester | Frühjahrsemester 2023 |
| Angebotsmuster | unregelmässig |
| Dozierende | Sepideh Alassi (sepideh.alassi@unibas.ch, BeurteilerIn) |
| Inhalt | 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. |
| Lernziele | 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 |
| Literatur | - 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 |
| Bemerkungen | Students should bring their own laptop to the course. |
| Teilnahmebedingungen | 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. |
| Unterrichtssprache | Englisch |
| Einsatz digitaler Medien | kein spezifischer Einsatz |
| Intervall | Wochentag | Zeit | Raum |
|---|---|---|---|
| wöchentlich | Donnerstag | 16.15-18.00 | Kollegienhaus, Hörsaal 119 |
| Datum | Zeit | Raum |
|---|---|---|
| Donnerstag 23.02.2023 | 16.15-18.00 Uhr | Kollegienhaus, Hörsaal 119 |
| Donnerstag 02.03.2023 | 16.15-18.00 Uhr | Fasnachstferien |
| Donnerstag 09.03.2023 | 16.15-18.00 Uhr | Kollegienhaus, Hörsaal 119 |
| Donnerstag 16.03.2023 | 16.15-18.00 Uhr | Kollegienhaus, Hörsaal 119 |
| Donnerstag 23.03.2023 | 16.15-18.00 Uhr | Kollegienhaus, Hörsaal 119 |
| Donnerstag 30.03.2023 | 16.15-18.00 Uhr | Kollegienhaus, Hörsaal 119 |
| Donnerstag 06.04.2023 | 16.15-18.00 Uhr | Ostern |
| Donnerstag 13.04.2023 | 16.15-18.00 Uhr | Kollegienhaus, Hörsaal 119 |
| Donnerstag 20.04.2023 | 16.15-18.00 Uhr | fällt aus |
| Donnerstag 27.04.2023 | 16.15-18.00 Uhr | Kollegienhaus, Hörsaal 119 |
| Donnerstag 04.05.2023 | 16.15-18.00 Uhr | Kollegienhaus, Hörsaal 119 |
| Donnerstag 11.05.2023 | 16.15-18.00 Uhr | Kollegienhaus, Hörsaal 119 |
| Donnerstag 18.05.2023 | 16.15-18.00 Uhr | Auffahrt |
| Donnerstag 25.05.2023 | 16.15-18.00 Uhr | Kollegienhaus, Hörsaal 119 |
| Donnerstag 01.06.2023 | 16.15-18.00 Uhr | Kollegienhaus, Hörsaal 119 |
| Module |
Modul: Creating, Analyzing and Visualizing of Data (Master Studienfach: Digital Humanities) Modul: Methoden der Gesellschaftswissenschaften (Masterstudium: European Global Studies) |
| Leistungsüberprüfung | Lehrveranst.-begleitend |
| Hinweise zur Leistungsüberprüfung | 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. |
| An-/Abmeldung zur Leistungsüberprüfung | Anmelden: Belegen; Abmelden: nicht erforderlich |
| Wiederholungsprüfung | keine Wiederholungsprüfung |
| Skala | Pass / Fail |
| Wiederholtes Belegen | beliebig wiederholbar |
| Zuständige Fakultät | Philosophisch-Historische Fakultät, studadmin-philhist@unibas.ch |
| Anbietende Organisationseinheit | Digital Humanities Lab |