This week, you will learn about applications of Semantic Web Technologies for knowledge engineering. We will start with Ontology Design. In the same way as for Software Engineering, there exist various methodologies to develop ontologies. This is especially helpful, if you are developing large scale ontologies with a team of distributed knowledge engineers. We will talk about Ontological engineering in general and you will learn about the Ontology 101 methodology as a simple example of ontology design.
Ontology design is rather expensive in terms of time and cost. Therefore, technologies for automated support have been developed, as e.g. Ontology Learning. This ranges from supporting the knowledge engineer in the design process from the scratch to populating already existing ontologies with individuals from text documents. Furthermore, you will learn about Ontology Alignment, which basically describes the task of finding correspondences among different ontologies. This is important, because different ontologies might model the same knowledge.
Next you will learn about Linked Data Engineering, i.e. how to make use of Linked Data Resources, how to publish Linked Data, how to consume Linked Data. We will have a closer look at the Linked Open Data Cloud and you will learn about the basics of Linked Data programming. As an example task, we will program a little Linked Data application in python, where we make use of SPARQL.
The last parts of the lecture will introduce the task of Named Entity Resolution for mapping text data to semantic entities with the purpose of semantic annotation, followed by the application of semantic metadata in the Semantic and Exploratory Search process.