Knowledge Processing with Big Data and Semantic Web Technologies

Ali Hasnain, Naoise Dunne, Narumol Prangnawarat, Stefan Decker

United States
Knowledge Processing and Acquisition are important activities for Data Scientists in a world rich with large heterogeneous data sources. Big Data not only provide an important set of tools to acquire and capture knowledge for the working data scientist, but also for the Knowledge Acquisition researcher, enabling the processing of large data sources. Especially in combination with Semantic Web and Linked Data technologies these promises to enable the processing of large as well as semantically heterogeneous data sources and the capturing of new knowledge from those. In this tutorial we present the state of the art in Big Data processing, as well as the amalgamation with Linked Data and Semantic Web technologies to form a Knowledge Pipeline. We aim to provide useful information for the Knowledge Acquisition research community as well as the working Data Scientist.