With the maturity of crowdsourcing systems, new analysis possibilities appear where volunteers play a crucial role by bringing the implicit knowledge issued from practical and daily experience. At the same time, data warehouse and OLAP systems represent the first citizen of decision-support systems. They allow analyzing a huge volume of data according to the multidimensional model. The more the multidimensional model reflects the decision-makers' analysis needs, the more the DW project is successful. However, when volunteers are involved in the design of DWs, existing DW design methodologies present some limitations. In this work, the authors present the main features of volunteer data warehouse (VDW) design, and they study the main existing DW design methodology to find out how they can contribute to fulfil the features needed by this particular DW approach. To provide a formal framework to classify existing work, they provide a study of differences between classical DW users and volunteers. The paper also presents a set of open issues for VDW.