It is increasingly common to encounter materials researchers engaged in the collaborative analysis and transformation of large-scale scientific data over extended periods of time. A scalable system for managing, tracing, exploring and communicating the analysis of diverse scientific data is required for these researchers. Nowadays dataspaces systems offer a pay-as-you-go approach to data management, which offer services on the data in place, without losing the context surrounding the data. Thus, we define a model and architecture for a Virtual Dataspaces (VDS) capable of addressing this requirement. The automatic construction process of the Virtual DataSpaces Model (VDM) is described in detail for effectively organising multi-source and heterogeneous data resources. Furthermore, the dynamic evolution algorithm of VDS is analysed and designed for timely tracking of the life cycle of the data resources. Such a system could bring increases facilitating discovery, understanding and sharing of both scientific data resources. An application case in the field of materials engineering is described to evaluate the effectiveness of the proposed model.