Tourism is one of the most important economic sectors in Austria. Given the high internationality degree of Austrian visitors, the websites of regional tourism organizations (RTOs) are an essential source of information. A state-of-the-art tourism website should include semantic markup for touristic topics so that search engines and other intelligent software applications can access and understand the presented data. This paper empirically studies the usage of Semantic Web formats, ontologies and topics relevant for tourism on the websites of all 137 Austrian RTOs.
Data from relational web tables can be used to augment cross-domain knowledge bases like DBpedia, Wikidata, or the Google Knowledge Graph with descriptions of formerly unknown long-tail entities. In previous work, we have presented an approach to successfully assemble descriptions of long-tail entities from relational HTML tables using supervised matching methods and manually labeled class-specific training data in the form of positive and negative entity matches. Manually labelling training data is a laborious task given knowledge bases covering many different classes.
The timbr SQL Semantic Knowledge Platform enables creation of virtual knowledge graphs in SQL. The DBpedia version of timbr supports query of DBpedia in SQL and seamless integration of DBpedia data into data warehouses and data lakes.