The Extensible Markup Language (XML) has become a widely adopted data interchange format. With the rise of Linked Data published using the Resource Description Framework (RDF), a number of tools for transforming XML to RDF have been developed. Specifying XML to RDF mappings for these tools often requires skills in programming languages such as XSLT or XQuery. Moreover, these tools are rarely able to deal with large XML inputs. We introduce an XML to RDF transformation approach, which is based on mappings comprising RDF triple templates that employ simple XPath expressions. Thanks to the restricted XPath expressions, which can be evaluated against a stream of XML data, our implementation can handle extremely large input XML files. To process the XML input efficiently, we employ XML filtering techniques and a strategy for selecting relevant XML nodes to generate RDF triples from. We show that the time complexity of our mapping algorithm is linear in the size of the XML input and also prove its practical efficiency with an evaluation on large real-world data.
National Chung Hsing University, Taiwan, University of Bonn & Fraunhofer IAIS
www.cs.uni-bonn.de
National Chung Hsing University, Taiwan, University of Bonn & Fraunhofer IAIS
www.cs.uni-bonn.de
Professor and director
Leibniz Information Center for Science & Technology
https://www.tib.eu/en/
Following stations at the universities of Dresden, Ekaterinburg, Leipzig, Pennsylvania, Bonn and the Fraunhofer Society, Prof. Auer was appointed Professor of Data Science and Digital Libraries at Leibniz Universität Hannover and Director of the TIB in 2017. Prof. Auer has made important contributions to semantic technologies, knowledge engineering and information systems.
