Semantic Web Reasoning on the Internet Scale with Large Knowledge Collider

The latest advances in the Semantic Web community have yielded a variety of reasoning methods used to process and exploit semantically annotated data. However most of those methods have only been approved for small, closed, trustworthy, consistent, and static domains. In the last years, Semantic Web has been facing significant challenges dealing with the emergence of Internet-scale data-intensive application use cases. Still, there is a deep mismatch between the requirements for reasoning on a Web scale and the existing efficient reasoning algorithms over restricted subsets. This paper discusses the Large Knowledge Collider (LarKC), a platform, which focuses on supporting large-scale reasoning over billions of structured data in heterogeneous data sets. The architecture of LarKC allows for an effective combination of techniques coming from different Semantic Web domains by following a service-oriented approach, supplied by sustainable infrastructure solutions.