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After completing this course successfully, the students are capable of:
- Explaining the principles of Linked Data, comparing and applying the main standards of the Semantic Web stack: RDF, OWL, SPARQL, SHACL
- Explaining, comparing and applying data format standards for Semantic Web applications (RDF serializations): RDF/XML, TTL and JSON-LD
- Designing and evaluating semantic models by following an ontology engineering methodology for a specific application domain
- Creating Linked Data dataset(s) from scratch and storing in a triplestore
- Reusing existing dataset(s), either from an available triplestore or by converting (“triplifying”) existing non-Linked Data datasets
Developing and evaluating a Semantic Web application that is capable of querying different datasets for data analytics
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The Semantic Web (SW) is an extension of the World Wide Web to make Internet data machine-readable in a way that can be consumed and understood by machines. This is supported by standards that are set by the World Wide Web Consortium (W3C), which are organized in the SW stack. Linked Data (LD) are structured data interlinked with other data built upon the SW stack, enabling applications to share information in a way that can be automatically ‘understood’ by computers. Part of the vision of LD is to enable the Internet to behave as a “global database”, so technologies that use the SW standards have a high potential to facilitate web data to be processed by machines. For example, SW technologies, like semantic triplet databases (also known as “triplestores”), can support the conversion and storage of the original data into knowledge graphs that are useful for Artificial Intelligence systems.
This course aims at covering the main SW standards and technologies for LD. This is a project-based course offering conventional lectures and hands-on sessions (exercises and project) as main learning activities. During the course, students will apply the acquired knowledge in the practical project that involves the development (programming) of a SW application, including a case analysis, the creation of a new linked data dataset, ‘triplifying’ an existing dataset, linking them for integrated query and data analytics. The main topics of the course are the following:
- Web of data, Linked Data, and Linking Open Data (LOD)
- Semantic Web standards, e.g., RDF, RDF schema, OWL, SPARQL, JSON-LD, SHACL
- Knowledge graphs and basic concepts in logics
- Semantic resources, e.g., popular vocabularies and standards (SSN/SOSA, SAREF, IFO, Bioontology, schema.org)
- Data Analytics, Reasoning, Artificial Intelligence
Assessment
- Written examination
- Project Report
- Assignments
- Presentation(s)
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| Background knowledge on design science research methodology, and software engineering (design and programming). Specific knowledge on XML/JSON (and their schemas), and RESTful services. |
Previous knowledge can be gained by| It is recommended that students follow the course on Service-oriented Architecture with Web services (192652150) before or during this course. Although this is not a formal prerequisite for this course, the students should know how to program and deploy web services, and manipulate data in relational databases, so it is convenient if they already have this knowledge when they start this course. |
| Master Business Information Technology |
| | Required materialsCanvas| Selected papers, made available via Canvas |
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Recommended materialsBook| Semantic Web Services https://link.springer.com/book/10.1007/978-3-642-19193-0 |
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Instructional modesAssessment| Presence duty | | Yes |
| Assignment| Presence duty | | Yes |
| Lecture| Presence duty | | Yes |
| Practical| Presence duty | | Yes |
| Presentation(s)| Presence duty | | Yes |
| Self study without assistance| Presence duty | | Yes |
| Workgroup| Presence duty | | Yes |
| Workshop| Presence duty | | Yes |
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TestsWritten exam
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