Human History is composed of a continuous flow of events. Each of them can impact subsequent events and contribute to the evolution of human knowledge. Knowledge Graphs try to encode the information about facts and events, often falling short when representing the temporal evolution of this knowledge and tracking cause-effect flows. kFLOW aims to propose strategies for representing, extracting, predicting and using the information about event relationships and knowledge evolution. For achieving these goals, a Knowledge Graph of interconnected events and facts will be realised. This graph will be populated and exploited through developing specialised strategies for data modelling, information extraction, link prediction, incorrect triple detection and automatic fact-checking.