Abstract. The rising Data Web has brought forth the requirement to treat information as dynamically evolving aggregations of data from remote and heterogeneous sources, creating the need for intelligent management of the change-driven aspects of the underlying evolving entities. Datasets change in multiple levels, such as evolving semantics, as well as structural characteristics, such as their model and format. In this paper, we present an archiving system that is driven by the need to treat evolution in a unified way, taking into account change management, provenance, temporality, and querying, and we implement the archive based on a data model and query language designed specifically for addressing preservation and evolution management in the Data Web.