Current semantic Web reasoning systems do not scale to the requirements of their hottest applications, such as analyzing data from millions of mobile devices, dealing with terabytes of scientific data, and content management in enterprises with thousands of knowledge workers. In this paper, we present our plan of building the large knowledge collider, a platform for massive distributed incomplete reasoning that will remove these scalability barriers. This is achieved by (i) enriching the current logic-based semantic Web reasoning methods, (ii) employing cognitively inspired approaches and techniques, and (iii) building a distributed reasoning platform and realizing it both on a high-performance computing cluster and via "computing at home". In this paper, we will discuss how the technologies of LarKC would move beyond the state-of-the-art of Web scale reasoning.
['Dieter Fensel', 'F.A.H. van Harmelen', 'B. Andersson', 'P. Brennan', 'H. Cunningham', 'E. Della Valle', 'F. Fischer', 'Zhisheng Huang', 'Atanas Kiryakov', 'Tony Lee', 'Lael J. Schooler', 'Volker Tresp', 'S. Wesner', 'Michael J. Witbrock', 'Ning Zhong']
Towards LarKC: A Platform for Web-Scale Reasoning