Finding the achilles heel of the web of data using network analysis tools

Abstract

The Web of Data is increasingly becoming an important infrastructure for such diverse sectors as entertainment, government, e-commerce and science. The robustness of this Web of Data is now crucial. Prior studies show that this Web is strongly dependent on a small number of central hubs, making it highly vulnerable to single points of failure. In this paper, we present concepts and algorithms to analyse and repair the brittleness of the Web of Data. We take the betweenness centrality as a robustness-measure and determine which links should be added to theWeb of Data to decrease the centrality index of the network. We are able to determine such links by interpreting the question as a very large optimisation problem and deploying an evolutionary algorithm to solve this problem.