Striving for semantic convergence with fuzzy cognitive maps and graph databases

The exponentially rising amounts of urban data demand new conceptual and technical methods for their management and storage. The era of the Semantic Web requires a convergence toward commonly shared meanings. The combination of fuzzy cognitive maps with graph databases is a first approach to a solution. This article determines the basic requirements for the storing of fuzzy cognitive maps to test current graph databases for their structural suitability. Six out of 47 graph databases fulfill the requirements and are thus recommended for further research purposes. As a proof of concept, OrientDB is used to present how a semantic convergence can be reached through the combination of fuzzy cognitive maps and graph databases in a cognitive city by tackling fuzziness.