RDF mapping rules refinements according to data consumers' feedback

The missing feedback loop is considered the reason for broken Data Cycles on current Linked Open Data ecosystems. Read-Write platforms are proposed, but they are restricted to capture modifications after the data is released as Linked Data. Triggering though a new iteration results in loosing the data consumers' modifications, as a new version of the source data is mapped, overwriting the currently published. We propose a prime solution that interprets the data consumers' feedback to update the mapping rules. This way, data publishers initiate a new iteration of the Data Cycle considering the data consumers' feedback when they map a new version of the published data.