Arndt, NatanaelRadtke, NormanEibl, MaximilianGaedke, Martin2017-08-282017-08-282017978-3-88579-669-5Knowledge engineering is becoming more and more important and collaborative approaches are promising. Especially in science, collaborative knowledge engineering on research data is a key factor for success. We propose a three layered method for distributed collaboration in curation of RDF datasets with the aim to bring domain experts into the role to command the process. The method builds on the existing infrastructure and work-flows of software engineering. By adding an RDF layer on top of the Git infrastructure, the method is flexible in its adaption to various domains using domain specific editing interfaces.endistributed collaborationcollaborative curationquitgitSPARQL Updaterdf datasetdomain specificsemantic webdistributed version control systemknowledge engineering10.18420/in2017_1871617-5468