A good virtual Learning Space (LS) should convey pertinent learning information to the visitors at the most adequate time and locations to favor their knowledge acquisition. Considering the consolidation of the internet and the improvement of the interaction, searching, and learning mechanisms, we propose a generic architecture, called CaVa, to create virtual Learning Spaces building up on cultural institution documents. More precisely, our proposal is to automatically create ontology-based virtual learning environments. Thus, to impart relevant learning materials to the virtual LS, we propose the use of ontologies to represent the key concepts and semantic relations in an user- and machine-understandable format. These concepts together with the data (extracted from the real documents) stored in a digital storage format (XML datasets, relational databases, etc.) are displayed in an ontology-based learning space that enables the visitors to use the available features and tools to learn about a specific domain. According to the approach here discussed, each desired virtual LS must be specified rigorously through a domain specific language (DSL) that was designed and implemented. To validate the proposed architecture, three case studies will be used as instances of CaVa architecture. (C) 2016 The Authors. Published by Elsevier B.V.